Understanding Big Data and Artificial Intelligence

SHAIVI CHAPALGAONKAR | June 18, 2021 | 14 views

Data is an important asset. Data leads to innovation and organizations tend to compete for leading these innovations on a global scale. Today, every business requires data and insights to stay relevant in the market. Big Data has a huge impact on the way organizations conduct their businesses. Big Data is used in different enterprises like travel, healthcare, manufacturing, governments, and more.  If they need to determine their audience, understand what clients want, forecast the needs of the customers and the clients, AI and big data analysis is vital to every decision-making scenario. When companies process the collected data accurately, they get the desired results, which leads them to their desired goals.

The term Big Data has been around since the 1990s. By the time we could fully comprehend it, Big Data had already amassed a huge amount of stored data. If this data is analyzed properly, it would reveal valuable industry insights into the industry to which the data belonged.

IT professionals and computer scientists realized that going through all of the data and analyzing it for the purpose was too big of a task for humans to undertake. When artificial intelligence (AI) algorithm came into the picture, it accomplished analyzing the accumulated data and deriving insights. The use of AI in Big Data is fundamental to get desired results for organizations.

According to Northeastern University, the amount of data in the world was 4.4 zettabytes in 2013. By of 2020, the data rose to 44 zettabytes.

When there is this amount of data produced globally, this information is invaluable to the enterprises and now can leverage AI algorithms to process it. Because of this, the companies can understand and influence customer behavior. By 2018, over 50% of countries had adopted Big Data.

Let us understand what Big Data, convergence of big data and AI, and impact of AI on big data analytics. 

Understanding Big Data

In simple words, Big Data is a term that comprises every tool and process that helps people use and manage vast sets of data. According to Gartner, Big Data is a “high-volume and/or high-variety information assets that demand cost-effective, innovative forms of information processing to enable enhanced insight, decision-making, and process automation.”

The concept of Big Data was created to capture trends, preferences, and user behavior in one place called the data lake. Big Data in enterprises can help them analyze and configure their customers’ motivations and come up with new ideas for the creation of new offerings. Big Data studies different methods of extracting, analyzing, or dealing with data sets that are too complicated for traditional data processing systems. To analyze a large amount of data requires a system designed to stretch its extraction and analysis capability.

Data is everywhere. This stockpile of data can give us insights and business analytics to the industry belonging to the data set. Therefore, the AI algorithms are written to benefit from large and complex data.

Importance of Big Data

Data is an integral part of understanding customer demographics and their motivations.
When customers interact with technology in active or passive manner, these actions create a new set of data. What contributes to this data creation is what they carry with them every day - their smartphones. Their cameras, credit cards, purchased products all contribute to their growing data profile. A correctly done analysis can tell a lot about their behavior patterns, personality, and events in the customer’s life. Companies can use this information to rethink their strategies, improve on their product, and create targeted marketing campaigns, which would ultimately lead them to their target customer.

Industry experts, for years and years, have discussed Big Data and its impact on businesses. Only in recent years, however, has it become possible to calculate that impact. Algorithms and software can now analyze large datasets quickly and efficiently.The forty-four zettabyte of data will only quadruple in the coming years. This collection and analysis of the data will help companies get the AI insights that will aid them in generating profits and be future-ready.

Organizations have been using Big Data for a long time. Here’s how those organizations are using Big Data to drive success:

Answering customer questions

Using big data and analytics, companies can learn the following things:

• What do customers want?
• Where are they missing out on?
• Who are their best and loyal customers?
• Why people choose different products?

Every day, as organizations gather more information, they can get more insights into sales and marketing. Once they get this data, they can optimize their campaigns to suit the customer’s needs. Learning from their online habits and with correct analysis, companies can send personalized promotional emails. These emails may prompt this target audience to convert into full-time customers.

Making confident decisions

As companies grow, they all need to make complex decisions. With in-depth analysis of marketplace knowledge, industry, and customers, Big Data can help you make confident choices. Big Data gives you a complete overview of everything you need to know. With the help of this, you can launch your marketing campaign or launch a new product in the market, or make a focused decision to generate the highest ROI. Once you add machine learning and AI to the mix, your Big Data collections can form a neural network to help your AI suggest useful company changes.

Optimizing and Understanding Business Processes

Cloud computing and machine learning help you to stay ahead by identifying opportunities in your company’s practices. Big Data analytics can tell you if your email strategy is working even when your social media marketing isn’t gaining you any following. You can also check which parts of your company culture have the right impact and result in the desired turnover. The existing evidence can help you make quick decisions and ensure you spend more of your budget on things that help your business grow.

Convergence of Big Data and AI

Big Data and Artificial Intelligence have a synergistic relationship. Data powers AI. The constantly evolving data sets or Big Data makes it possible for machine learning applications to learn and acquire new skills. This is what they were built to do. Big Data’s role in AI is supplying algorithms with all the essential information for developing and improving features, pattern recognition capabilities.

AI and machine learning use data that has been cleansed of duplicate and unnecessary data. This clean and high-quality big data is then utilized to create and train intelligent AI algorithms, neural networks, and predictive models.

AI applications rarely stop working and learning. Once the “initial training” is done (initial training is preparing already collected data), they adjust their work as and when the data changes. This makes it necessary for data to be constantly collected.

When it comes to businesses using this technology, AI helps them use Big Data for analytics by making advanced tools accessible and obtainable to help users gain insights that would otherwise have been hidden in the huge amount of data. Once firms and businesses gain a hold on using AI and Big Data, they can provide decision-makers with a clear understanding of factors that affect their businesses. 

Impact of AI on Big Data Analytics

AI supports users in the Big Data cycle, including aggregation, storage, and retrieval of diverse data types from different data sources. This includes data management, context management, decision management, action management, and risk management.

Big Data can help alert problems and help find new solutions and get ideas about any new prospects. With the amount of information stream that comes in, it can be difficult to determine what is important and what isn’t. This is where AI and machine learning come in. It can help identify unusual patterns in the processes, help in the analysis, and suggest further steps to be taken.

It can also learn how users interact with analytics and learn subtle differences in meanings or context-specific nuances to understand numeric data sources. AI can also caution users about anomalies, unforeseen data patterns, monitoring events, and threats from system logs or social networking data.

Application of Big Data and Artificial Intelligence

After establishing how AI and Big Data work together, let us look at how some applications are benefitting from their synergy:

Banking and financial sectors

The banking and financial sectors apply these to monitor financial marketing activities. These institutions also use AI to keep an eye on any illegal trading activities. Trading data analytics are obtained for high-frequency trading, and decision making based on trading, risk analysis, and predictive analysis. It is also used for fraud warning and detection, archival and analysis of audit trails, reporting enterprise credit, customer data transformation, etc.

Healthcare

AI has simplified health data prescriptions and health analysis, thus benefitting healthcare providers from the large data pool. Hospitals are using millions of collected data that allow doctors to use evidence-based medicine. Chronic diseases can be tracked faster by AI.

Manufacturing and supply chain

AI and Big Data in manufacturing, production management, supply chain management and analysis, and customer satisfaction techniques are flawless. The quality of products is thus much better with higher energy efficiency, reliable increase in levels, and profit increase.

Governments

Governments worldwide use AI applications like facial recognition, vehicle recognition for traffic management, population demographics, financial classifications, energy explorations, environmental conservation, criminal investigations, and more.

Other sectors that use AI are mainly retail, entertainment, education, and more.

Conclusion

According to Gartner’s predictions, artificial intelligence will replace one in five workers by 2022. Firms and businesses can no longer afford to avoid using artificial intelligence and Big Data in their day-to-day. Investments in AI and Big Data analysis will be beneficial for everyone. Data sets will increase in the future, and with it, its application and investment will grow over time. Human relevance will continue to decrease as time goes by.

AI enables machine learning to be the future of the development of business technologies. It will automate data analysis and find new insights that were previously impossible to imagine by processing data manually. With machine learning, AI, and Big Data, we can redraw the way we approach everything else.

Frequently Asked Questions

Why does big data affect artificial intelligence?

Big Data and AI customize business processes and make better-suited decisions for individual needs and expectations. This improves its efficiency of processes and decisions. Data has the potential to give insights into a variety of predicted behaviors and incidents.

Is AI or big data better?

AI becomes better as it is fed more and more information. This information is gathered from Big Data which helps companies understand their customers better. On the other hand, Big Data is useless if there is no AI to analyze it. Humans are not capable of analyzing the data on a large scale.

Is AI used in big data?

When the gathered Big Data is to be analyzed, AI steps in to do the job. Big Data makes use of AI.

What is the future of AI in big data?

AI’s ability to work so well with data analytics is the primary reason why AI and Big Data now seem inseparable. AI machine learning and deep learning are learning from every data input and using those inputs to generate new rules for future business analytics.

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Orbica is New Zealand’s newest and most progressive location data intelligence consultancy. We specialise in enabling business by harnessing and augmenting the data you collect and transforming it into an asset. Whether your data is sourced from the field, earth orbit, 3rd parties or your workplace Orbica can help you use it to gain real-time visibility of your organisation and control of your decisions. With maps, graphics, infographics, three dimensional worlds – and by constantly searching for new ways to innovate – Orbica creates functional engagement and real value.

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BUSINESS STRATEGY

Predictive Analytics: Implementation in Business Processes

Article | May 31, 2022

Knowledge is power in business, and knowing what will happen in the future is a superpower. When data analytics, statistical algorithms, AI, and machine learning are combined, this superpower, also known as predictive analytics, becomes a skill that can significantly influence on a company's choices and outcomes. Predictive analytics is the use of modern analytical tools. For example, machine learning concludes about the future based on historical data. Businesses can consider application of predictive analytics tools and models to forecast trends and generate accurate future predictions by leveraging historical and current data. Let’s look at the top three reasons why predictive analytics is important for your business. Why is Predictive Analytics Important for Businesses? Businesses are looking at predictive analytics to help them solve challenges and discover new opportunities. 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Predicting customer requirements accurately is a huge opportunity for businesses. Companies can use AI and predictive analytics models to figure out what customers will do based on data instead of guesswork. Pricing Optimization Predictive business analytics can help companies improve pricing optimization quickly and affordably. A business can use predictive analytics to figure out how to make a product more affordable in the future by looking at past data, industry trends, competitive prices, and other data sources. Each customer provides a unique value to the products. To add to the complexity, a consumer's value of a product may vary depending on the purchase circumstances and environment. Simplicity in pricing misses opportunities and can result in a significant drop in revenue. Product information, consumer segmentation, and purchase circumstances are all enhanced by predictive analytics. Businesses can use this data to uncover trends and patterns to help them price more profitably. Predicting Growth and Market Trends Businesses can use predictive market analysis to decipher existing and future market trends. With this data, businesses can develop a plan to maximize opportunities, expand market share, and sustain disruption and new competition. Companies can use it to detect unmet customer demand and fill any gaps. Consumption sentiment is revealed through social media data. A product that does not match customer demand creates a market opportunity for a new product or service. Predictive market analysis can uncover customer perceptions of a product or service and unmet consumer demands. Predictive business analytics helps businesses better understand their customers, meet their needs, and find new ways to earn revenue and grow. Example: Reu La La Uses Predictive Analytics to Increase its Revenue by 10% You often hear about giant enterprises like Amazon, Airbnb, Microsoft, Google, and others utilizing predictive analytics to extend their reach, boost sales, and more. Today let’s look at Reu La La and how they used predictive analytics to enhance their revenue. Rue La La, a boutique retailer, often needs to predict sales and fix pricing for products being sold for the first time in its online store with no existing sales data. They observed that many products were either sold out within the first few hours of release or did not sell, which lead to revenue loss. Rue La La took action by creating a set of quantitative qualities for its items and predicting future demand by utilizing historical sales data. They used statistical and computing technologies, such as regression analysis and machine learning, to create a demand forecast and pricing optimization model. In partnership with the Massachusetts Institute of Technology, they created an automated price decision assistance tool. Revenue increased from 10% to 13% across all departments because they used the pricing tool's proposed optimal rates. Conclusion “As data piles up, we have ourselves a genuine gold rush. But data isn’t the gold. I repeat, data in its raw form is boring crud. The gold is what’s discovered therein.” Eric Siegel You can consider the predictions that predictive analytics makes as gold, but, using predictive analytics is like a crystal ball that shows the future. You can look into the future, prevent issues in your company from escalating, and recognize profitable possibilities. If you haven't started leveraging predictive analytics, start by experimenting with it on a modest scale and gradually build up as you acquire expertise and observe positive outcomes. FAQ How can Predictive Analytics Improve Performance Measurement? Predictive analytics improves performance measurements by expanding an organization's understanding of the important performance drivers. It also helps with the weighting of different performance metrics based on how important they are. What Are the Four Steps in Predictive Analytics? In simple terms, predictive analytics involves four steps: creating a baseline prediction, assessing it, adding assumptions, and building a consensus demand plan. To do so, we must first choose a modeling technique, create a test design, then construct the model, evaluate the mode, and achieve alignment. What Are the Three Different Types of Predictive Analytics? Businesses utilize three forms of analytics to drive their decision-making: Descriptive analytics — tells something that has already happened; Predictive analytics — shows what can happen; Prescriptive analytics — tells what should happen in the future

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BIG DATA MANAGEMENT

Embrace Corporate Performance Management to Enhance Your Business

Article | June 1, 2022

When it comes to improving business performance, quite a bit of jargon gets thrown around. Corporate performance management (CPM), for example, is often used to refer to business performance management and enterprise performance management, but these terms don't always refer to the same thing. CPM improves a company's capability. It helps the company enhance three fundamental values: performance monitoring, information delivery, and performance effectiveness. These values assist in understanding, improving, and managing the business. Within an integrated ecosystem, a corporate performance management system coordinates the performance of managers, employees, customers, and suppliers. Information access and strategic planning are the foundations of corporate performance management. 3 Reasons Why You Need Corporate Performance Management (CPM) In the era of exploding business intelligence, businesses need to embrace process automation. CPM may profoundly impact your team's productivity, coherence, insight, and more. CPM functions are critical to the C-suite and the long-term success of an organization. As a result, several businesses have developed departments solely dedicated to strategy and performance management. Let's look at the top reasons why you should use CPM for your business. Addressing Challenges in Financial Data Compiling your financial data takes time. To see and organize your financial data easily and quickly, you can use CPM software to connect with your ERP system. This application will also make the finance team's job simpler. It will be easier to understand and manage the projected estimates and how important they are. Real-time Feedback Smart dashboards in business performance management or CPM software provide every quantifiable statistic that a management team will need to use in its decision-making. Even though there are so many different types of data, it can be a good thing to read and use it as changes happen in real-time in the company. Streamlined Reporting Most businesses have several individuals involved in performance management, right from C-level executives to back-office administrators. Although not everyone is actively participating in the performance management process, many users need access to and analysis of reports. CPM technology for a business focuses on a single source of information or data. That is why it provides greater control over it. It also gives more control and security over the results that come out of the process. Who Uses CPM? Earlier, CPM was primarily used by businesses with more than 1,000 workers. However, due to the affordability and simplicity of next-generation CPM solutions, dynamic and ambitious organizations from the startup phase to the enterprise level are now utilizing them. This is one of the prime reasons for the rapid increase in the CPM software market. Companies that sense an opportunity to grow, large businesses that operate globally, organizations that merge with others, and businesses that strive to improve company performance are the most likely to use CPM. Overcoming the Corporate Performance Management Challenges When a business imparts great performance management throughout the workplace, critical expectations and desired outcomes must be set. Also, this does not always go as planned. As a result, CPM presents significant challenges that need immediate attention, as stated below. Strategic Alignment This involves ensuring that all organizational processes and essential components, such as finances, project and program management, risk management, etc., align with the primary goal. Smart Automation A poorly implemented CPM will result in complete failure. 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There are graphical scorecards and dashboards for displaying corporate information in the CPM software. Forecasting, budgeting, and planning are some of the features that come with the software. What Are the Primary Corporate Performance Metrics? CPM is an aspect of business intelligence (BI) that includes monitoring and controlling a company's performance based on key performance indicators (KPIs) such as revenue, ROI, overhead, and operational expenses. What Is the Difference Between CPM and EPM? CPM concentrates on delivering a company-wide performance management solution, especially for the organization's finance department. EPM focuses on the overall performance of the organization, going beyond the finance departments to sales, marketing, supply chain, and other areas.

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BUSINESS STRATEGY

The Art of Developing a Successful Business Intelligence Strategy

Article | May 13, 2022

Business intelligence, or the art of using data to discover insights, has become a crucial part of developing business strategy for leading organizations, including government agencies, Fortune 500 companies, and educational institutions. Businesses that want their operations to be more informed and backed by data must use business intelligence. This is done with the help of a BI strategy. A BI strategy is a blueprint that helps you decide how to use data in your company. You need a business intelligence strategy, as merely choosing a BI technology is not enough to leverage the benefits of business intelligence. Many organizations struggle with implementing business intelligence solutions because of a lack of a proper BI strategy. The Downside of Not Developing a BI Strategy A business intelligence strategy will help you to address all your needs and problems related to data, develop a cohesive system, and maintain it. You might encounter various problems if you don’t have a BI strategy. Here are some of the pitfalls of not having a business intelligence strategy, which you can simply avoid by developing one. Reduced Possibility of Successful BI Implementation According to Gartner, business intelligence adaptation is only around 30% in most industries. If an organization wants to avoid being one of those who haven’t implemented BI, a pre-planned BI strategy is the key to successful adoption. A company that lacks knowledge about the system they want to implement is at a higher risk of failing. Risk of Overspending A company that does not have a BI strategy is likely to overspend compared to those with a business intelligence plan. This is because there are no strict guidelines to follow. A company without a business intelligence strategy will agree to whatever a vendor tells them about their company or industry requirements. Later, if they don’t use that feature because they don’t require it, paying more for that feature will be a complete waste of money. Wastage of Time A company without a business intelligence strategy has to begin all over again with its business intelligence software search. Failure to adopt business intelligence tools can also be frustrating for the employees because of the inconvenience caused. This emphasizes that having a defined business intelligence plan is always better. Steps to Build a Business Intelligence Strategy The business intelligence strategy should align with the overall business goals resulting in an exponential growth. So, let’s start with the five steps to developing a successful business intelligence strategy. Determine Business Intelligence Strategic Objectives The first step towards developing a BI strategy is identifying and highlighting the strategic objectives. Next, the business intelligence team must evaluate the unique business objectives, align them with relevant data and resources, and recognize processes that empower the company. Conduct Cost and Benefits Analysis Let’s assume you have ten possible BI software options but which one will help you deliver the larger business objectives. How will you prioritize and choose your platform? In such a case, conducting a cost and benefits analysis is always helpful. The steps for conducting the analysis are as follows: Set a framework for your analysis Add the cost of implementation Consider the margin impact per product Check if the cost and benefit projection is favorable for you Analyse the need for additional resources or re-alignments to be made with existing resources Choose a Business Intelligence Platform Business intelligence software can do a lot, but it is not the entire BI strategy. Now, that you have identified the strategic objectives and have conducted a cost and benefit analysis, you can consider the following components while choosing a BI platform: Data access and the viewing of useful content Data interactivity within a visual interface The ability to go deeper into data on your own and find new insights Promote new insights into a governed environment Collaborate on data analysis and visualized analytics Build a Strong Team You should never forget that only a strong team with a data and analytics mindset can ensure a successful business intelligence implementation. They must be tech-savvy to handle complex IT issues and should be familiar with convoluted statistics and mathematics. They should also have a creative approach to problem-solving. Create a Business Intelligence Roadmap The BI team needs to develop a roadmap for the implementing a business intelligence strategy. You can consider the following things to create a BI roadmap: Keep track of deliverables and dependencies Keep a watch on the future and make adjustments to your strategy as required Be proactive instead of reactive Case Study: Customer Satisfaction Boosted by Business Intelligence Expedia is the parent company of Hotwire and TripAdvisor, all the three are leading tourism companies. Expedia was facing challenges related to customer satisfaction, which is extremely crucial to the company's mission, strategy, and success. The online experience should resemble a pleasant journey, but the company had no access to the customer's voice. To tackle this issue, the organization had to manually aggregate heaps of data with insufficient time for analysis. The customer satisfaction team was able to examine consumer data using business intelligence and correlate results to ten objectives that were directly tied to corporate priorities. KPI owners create, monitor, and analyze data to spot trends or patterns. As a result, the customer service team can now monitor how well it is performing against KPIs and take corrective action as needed. In addition, the data can be used by other departments. Conclusion If done correctly, a strong business intelligence strategy can bring irresistible power to your company. You can prevent yourself from overspending, save time and gain a competitive advantage by having an approach based on BI strategy while selecting BI software. FAQ What is a business intelligence roadmap? Business intelligence managers and their teams utilize business intelligence roadmaps to visualize all aspects of BI, including analytics, adoption, data, and training. Plan how to use business intelligence to increase efficiency and performance across your organization. What is the business intelligence lifecycle? Business intelligence lifecycle management is a way to design, build, and manage BI that includes business customers. It focuses on making data models, database objects, data integration mappings, and front-end semantic layers right away from input from business users. How does Netflix utilize business intelligence? Netflix utilizes traditional business intelligence tools and big modern data technologies. As a result, it creates algorithms that predict what consumers are most likely to watch. It also makes extensive use of open-source software in this regard.

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BUSINESS INTELLIGENCE

Embedded Business Intelligence- A Guide to an Upgraded BI

Article | April 12, 2022

Businesses are becoming more data-driven, and the potential to use data and analytics to differentiate market leaders is becoming increasingly important. Customers are demanding actionable insights into the apps, products, and services they use daily, and businesses of all sizes are trying to meet these demands. Product managers understand they must provide their consumers with concrete insights derived from processed data. However, creating these features from scratch can sometimes be a difficult task. The answer is simple: add an analytics platform into your core product, like integrated business intelligence. Embedding an analytics system may also help a company get more value out of the data it has already spent time acquiring, keeping, and analyzing. Embedded business intelligence is among the most important use cases in the broader data analytics sector, as companies leverage the technology to build extranet apps and give analytics as part of a larger business application. Those looking to integrate analytics tools into their existing business operations must prioritize their requirements in order of importance. Why Should Businesses Choose Embedded Business Intelligence? Embedded business intelligence (Embedded BI) is the future of BI, because it makes it easy for your employees to use dashboards and make data-based decisions as they go about their work. Let's look at some of the reasons why you should opt for embedded business intelligence. Insightful Decision-Making Embedding BI allows you to leverage insights, making data more accessible irrespective of technical skills. Embedded analytics tools provide you with quick access to data that can help you make better business decisions. If “glitches” show up on the radar, strategic decision-makers can raise the alarm, assess the threat, develop remedies, and come up with solutions, and change the business course. Create an Effortless Workflow According to MarTech Today and Blissfully, "businesses with fewer than 50 employees have approximately 40 applications in total." The truth is that current employee operations are complicated and scattered across several platforms. BI platforms aren't a silver bullet for this challenge. Embedded BI, on the other hand, can be beneficial. Embedded BI eliminates the need for your sales executive to make choices and streamlines their workflow. It seamlessly integrates the data into this team's existing tool process with minimal disruption. Reduce your Reliance on Developers Businesses that depend entirely on their overburdened developers to implement an analytics solution will invariably create a data bottleneck. Embedded BI tools reduce this barrier and encourages everyone who works with embedded data to be more flexible and iterative. With the help of embedded business intelligence, you can check and analyze business data and adjust visuals on the go by utilizing dynamic data visualization. Drill-down, filtering, and search are interaction options available on these embedded BI tools, allowing to freely explore reports and dashboards and extract crucial business insights. Should You Build In-House Embedded BI or Buy a Third-Party? When it comes to deploying an embedded BI tool, you have two options. Organizations can either develop their products in-house or buy them from a third party. Building an embedded BI platform from scratch might take a long time and may be costly like most businesses with software as their key competence, general companies should first explore commercially available embedded BI solutions. Also, purchasing embedded BI allows businesses to focus on their core competencies while leveraging the tools to deliver embedded BI features to users faster. Top Embedded Business Intelligence Tools for C-Suite (Include cases) Many embedded BI tools are available in the market but choosing the most appropriate tool from among them is a major task. So, to end your search for the perfect embedded BI tool, you can check out the list below. We have also included case studies of these embedded business intelligence applications for you to make a better decision. Sisense BI Helps Crunchbase Get Access to the Right Data across the Organization In the business world, Crunchbase is the most important database, and they needed a powerful platform to get all their data together, so they went with Sisense BI. Crunchbase was able to take its analytics to the next level using Sisense for Cloud Data Teams, which allowed them to access their data, from their marketing stack to Salesforce platforms to website impression data, to create a holistic view of their business and customers. It's also good for Crunchbase's marketing team because the interface of Sisense is easy to use. This makes it easy for business users to understand data on their own and use it for decision making. Microsoft Power BI Helps Heathrow Airport in Making Travels Less Stressful Heathrow Airport serves as the U.K.'s international gateway. Heathrow Airport serves 80 million passengers each day, and the airport is utilizing Microsoft Power BI and Microsoft Azure to make travel less stressful for travelers. With the help of Power BI, Heathrow Airport gets real-time operational data for its employees. It enables to assist passengers in navigating the airport despite bad weather, canceled flights, and other delays. For example, a disturbance in the jet stream caused a delay of 20 flights, resulting in 6,000 more passengers arriving at the airport at 6:00 p.m. Previously, employees at immigration, customs, luggage handling, and food services would not be aware of the unexpected passengers until they arrived, forcing them to make do with what they had. But now, all these employees are notified one to two hours prior so that they can arrange extra workers, buses, food, and other resources to assist with the inflow. Qlik Sense Helps Tesla Users Get Information About Tesla SuperCharge Stations Tesla customers use a Qlik Sense application to track the locations of Tesla supercharger stations and obtain information about them. The software uses real-world road network computations and overlap predictions based on Tesla vehicles' typical battery range. This app needs to work with Qlik GeoAnalytics because it displays supercharging stations on a map. Charger status is also displayed on the dashboard. You can make choices based on where you are on the dashboard, and the program will respond based on the associations between data sets. Closing Lines Embedded business intelligence has significant potential for small firms and enterprise powerhouses alike. Embedded analytics outperforms previous solutions in extracting the most value from your data and enabling today's crucial business choices. However, long-term use of embedded analytics will require a significant amount of work on the part of the C-suite. The C-suite will have a positive influence and assure continued analytics success by applying predictive analytics, integrating machine learning, and encouraging a data-driven culture. FAQ Is there a limit to embedding analytics into existing applications? Embedded BI products have less limitations than independent tools and are mostly more capable. Machine learning, NLP, and artificial intelligence (AI) are included in the current, more modern generation of embedded systems, although these abilities are generally not included in standalone solutions. What should purchasers keep in mind while selecting a vendor? Users who have only used a typical BI or data analytics tool should be wary of colorful charts and data visualizations. Buyers must think about the long term, particularly when it comes to product maintenance, making changes across instances, and offering a simple yet tailored experience to the end-user. Are embedded business intelligence solutions easy to set up? The beauty of embedded analytics and BI solutions is quick and simple to deploy. You can either add them to an existing system or design a new one based on your requirements.

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Orbica

Orbica is New Zealand’s newest and most progressive location data intelligence consultancy. We specialise in enabling business by harnessing and augmenting the data you collect and transforming it into an asset. Whether your data is sourced from the field, earth orbit, 3rd parties or your workplace Orbica can help you use it to gain real-time visibility of your organisation and control of your decisions. With maps, graphics, infographics, three dimensional worlds – and by constantly searching for new ways to innovate – Orbica creates functional engagement and real value.

Related News

BIG DATA MANAGEMENT

Synopsys Launches the Era of Smarter SoC Design with ML-Driven Big Data Analytics Technology

Synopsys | June 03, 2022

Driving greater design productivity by harnessing previously untapped design insights with machine learning technology, Synopsys, Inc. (Nasdaq: SNPS) today announced a critical expansion of its EDA data analytics portfolio with the introduction of Synopsys DesignDash design optimization solution. As a complementary product to Synopsys' market-leading Digital Design Family and Synopsys DSO.ai™, the award-winning AI-driven design-space-optimization solution, Synopsys DesignDash is a comprehensive data-visibility and machine intelligence-guided design optimization solution that enables unmatched productivity in advanced SoC design. The Synopsys DesignDash solution delivers a real-time, unified, 360-degree view of all design activities for faster decision making, a deeper understanding of run-to-run, design-to-design and project-to-project trends, and enhanced collaboration in the SoC development process. "As a leading supplier of SoCs that are powering and transforming numerous high-impact industries, we pride ourselves on being able to push the limits of achievable device performance while also accelerating our customers' time-to-market," said Hiroshi Ikeda, director, Methodology Development Office, Global Development Group at Socionext. "We're very excited by the Synopsys DesignDash analytics solution as a systematic way to capture, consume and evaluate our vast design activity in a scalable way, enabling us to share and transfer expert knowledge across our worldwide design teams to enhance productivity and efficiency." Unlocking the Potential Within Vast Volumes of Digital Design Data The digital design flow holds a wealth of information from myriad sources that, properly utilized, could help teams optimize increasingly complex designs faster. According to Gartner® Inc., "By 2023, overall analytics adoption will increase from 35% to 50%, driven by vertical- and domain-specific augmented analytics solutions."1. The introduction of Synopsys DesignDash is the latest step in a multi-year, multi-disciplinary development effort to address the need for exponential gains in design productivity in the face of massive growth in system complexity, shrinking market windows and an increasingly challenging resource landscape. The cloud-optimized Synopsys DesignDash design optimization solution greatly enhances design productivity by: Providing extensive real-time design status through powerful visualizations and interactive dashboards. Deploying deep analytics and machine learning to extract and reveal actionable understanding from vast volumes of structured and unstructured EDA metrics and tool-flow data. Quickly classifying design trends, identifying design limitations, providing guided root-cause analysis and delivering flow consumable, prescriptive resolutions. With deeper design insights, designers can achieve more effective debug and optimization workflows, realize improved quality of results (QoR) and significantly extend overall design- and project-flow efficiency and effectiveness. This extensive insight and real-time visibility additionally deliver comprehensive resource monitoring and tracking that spans all design activities, enabling more data-driven management and risk mitigation throughout the design process. Synopsys DesignDash is natively integrated with the Synopsys Digital Design family of products for seamless data capture, resulting in insights that further accelerate the path towards design closure. The solution complements the Synopsys SiliconDash product, part of the Synopsys Silicon Lifecycle Management Family, forming a pre-silicon to post-silicon data continuum, maximizing opportunities for valuable data analysis across the complete design-to-silicon lifecycle. "SoC complexity across all application niches continues to rise as more functionality and performance is required. "Through the data analytics and machine learning capabilities of the Synopsys DesignDash technology, engineering teams now have an efficient way to share and utilize valuable insights that would otherwise take hours of manual work to compile or, in some cases, not be accessible." Karl Freund, founder, and principal analyst at Cambrian-AI Research "The semiconductor industry needs a dramatic improvement in design process productivity. Improving the quality and speed of engineering decisions with a comprehensive EDA data analytics platform is a critical step in this direction," said Sanjay Bali, vice president of Marketing and Strategy for the Silicon Realization Group at Synopsys. "Synopsys DesignDash unlocks the potential of the significant and growing volumes of EDA metrics and design-flow data, heralding a new era in smarter IC design by deploying an expanse of advanced data analytics and targeted machine learning to effectively guide design teams to achieve or exceed their product goals and schedules." About Synopsys Synopsys, Inc. is the Silicon to Software™ partner for innovative companies developing the electronic products and software applications we rely on every day. As an S&P 500 company, Synopsys has a long history of being a global leader in electronic design automation (EDA) and semiconductor IP and offers the industry's broadest portfolio of application security testing tools and services. Whether you're a system-on-chip (SoC) designer creating advanced semiconductors, or a software developer writing more secure, high-quality code, Synopsys has the solutions needed to deliver innovative products.

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BUSINESS INTELLIGENCE

BigID launches Data Insights Studio to close the gap between insight and action

BigID | April 08, 2022

BigID, the leading data intelligence platform that enables organizations to know their enterprise data and take action for privacy, security, and governance, today launched Data Insights Studio, a new capability that provides rich and insightful reporting and analytics about the state of data across the entire organization. Data Insights Studio gives privacy, security, and governance teams the power to create rich, insightful, and actionable reporting best suited for their organization and easily monitor relevant metrics to better assess the progress of their data initiatives. Data Insights Studio seeks to close the gap between insight and action so that teams have the speed to make the best decisions about their data. BigID Data Studio enables organizations to know when and where to take action on their data through accurate reporting and analytics. Capabilities include: Driving proactive executive decision-making with actionable insights about data security, privacy, and governance initiatives. Actively monitoring trends, metrics, and important KPIs over time while also allowing for forecastability. Empowering users through self-service, configurable reporting, and alleviating the burden off of IT admins. Centralizing data intelligence holistically for organizations with global data footprints. "Data Insights Studio brings a whole new meaning to data intelligence. We're giving customers the power to visualize their data like never before. We strongly believe that providing easy and customizable reporting of how metadata changes over time and across multiple sites, as well as an ability to analyze trends and monitor critical KPIs, is the key to facilitating and accelerating better data management and value on data across the organization." Nimrod Vax, Co-Founder and Head of Product at BigID Reporting can take on various forms and provides immense value to help illustrate the direction and progress of initiatives. Unfortunately, developing proper executive reporting that addresses the needs of an organization can be nuanced and cumbersome. IT teams are often required to manually create reports and analytics to fit their needs, a method that not only fails to scale well but also lacks proper speed and accuracy to drive the right decisions. Data Insights Studio aims to close the gap between insight and action so that IT teams have the agility to act on their data with certainty. About BigID BigID's data intelligence platform enables organizations to know their enterprise data and take action for privacy, protection, and perspective. Customers deploy BigID to proactively discover, manage, protect, and get more value from their regulated, sensitive, and personal data across their data landscape. BigID has been recognized for its data intelligence innovation as a 2019 World Economic Forum Technology Pioneer, named to the 2021 Forbes Cloud 100, the 2021 Inc 5000 as the #19th fastest growing company and #1 in Security, a Business Insider 2020 AI Startup to Watch, and an RSA Innovation Sandbox winner.

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BIG DATA MANAGEMENT

Fluree Announces Significant Momentum in Digital Trust and Privacy Collaboration, Strategic Partnerships and Developer Adoption, on the Path to Web3

Fluree | December 27, 2021

Fluree, provider of the Web3 data platform, today announced significant momentum as the technology of choice for privacy-preserving data ecosystems. Fluree’s immutable semantic graph database played a key role in a wide range of projects in 2021, including secure academic credentials for projects funded by the Department of Education, a tamper-proof and fair blockchain-backed election, and off-chain data storage for Cardano, the sixth-largest cryptocurrency in the world. “It’s inspiring to see the ways that developers are taking advantage of Fluree’s ability to deliver trust, semantic context and security to data projects,” said Fluree Co-CEO and Co-Founder Brian Platz. “Support for our platform is at an all-time high, driven by data-centric architecture that can power trusted, interoperable data ecosystems.” “Mainstream adoption of Web3 — the decentralized Internet of data — is on the horizon. As the rise of data ecosystems are met with privacy, trust and interoperability challenges, Fluree is uniquely poised to become the infrastructure of choice in the emerging Web3 market,” said Dan Malven, Managing Director at 4490 Ventures. Surge in Developer Adoption: 500% Growth in 2021 Fluree’s open source technology grew 500% in users in 2021, topping 100,000 total downloads to date as it becomes the technology of choice for privacy-preserving data ecosystems. Key use cases in verifiable credentials, education technology, enterprise knowledge graphs, and blockchain applications continue to emerge. Fluree’s recently overhauled developer portal and growing Slack community accommodates the influx in developer adoption, prioritizing the Fluree developer experience and community. Fluree’s rise in both developer adoption and strategic partners has been recognized, winning local awards such as Tech Tribune’s Best Tech Startup in Winston-Salem to being recognized as CRN’s Coolest Database System Company of 2021 as well as a winner of Business Intelligence Group’s Fortress Cyber Security Award. Digital Privacy and Verifiable Credentials for the Public Sector, Supporting Education and Health Care Improvements Verifiable credentials and decentralized identifiers have become a central theme in rising Fluree use cases across education ecosystems and healthcare. As the world begins to understand the value of privacy in digital ecosystems, organizations have chosen Fluree to power solutions that return ownership of information to consumers. Education Credentials: Two winning projects of the American Council of Education’s Blockchain Innovation Challenge, funded by the Department of Education, are using Fluree's technology to transform credentialing in academic ecosystems. The LifeLong Learner Project focuses on providing teachers with a wallet to store and present certifications as they move throughout their careers. The UnBlockED project is focused on creating an open transfer exchange that will empower college students by streamlining transfer credit recognition. In both projects, Fluree’s technology provides the foundation for the exchange of secure and interoperable verifiable credentials across owners, issuers, and third-party institutions. Key partners within these initiatives include the University of Arizona, the Gardner Institute, and Georgia Tech. Healthcare Credentials: Pulse Connect has partnered with Fluree to build verifiable credential solutions for patients and health providers. This will help support verification requirements around vaccine credentialing in view of increasing vaccine mandates. Strategic Partnerships: Supporting Cryptocurrency Advancements, Tamper-Proof Elections and Codifying Unstructured Data Much of Fluree’s 2021 momentum stems from Fluree’s growing partner ecosystem, which recently won the CRN’s “Channel Chiefs Award.” Examples of rising stars in Fluree’s Partner Ecosystem include: Building a Metadata Sidechain Solution for the Sixth Largest Cryptocurrency: The community supporting the high-ranking cryptocurrency blockchain platform Cardano selected Ikigai Technologies and Fluree to power Logosphere. The Logosphere project proposes Fluree as an "off-chain decentralized app (dApp) data storage solution" for the metadata related to Cardano transactions. Instead of placing data into siloed databases, Fluree will act as a secure and interoperable metadata layer for dApp developers. This will enable a new class of data-driven dApps, such as non-fungible token (NFT) exchanges, decentralized knowledge graphs, and other data-centric Web3 applications. Powering the World’s First End-to-End Blockchain Election: Marzex.tech technologies delivered a Fluree-powered digital voting platform for the International Islamic University of Malaysia. The digital platform used Fluree’s backend to successfully register identities, facilitate private voting, and thwart efforts to tamper with the election. Turning Text into Trusted, Interoperable Data: Fluree integrated with Lead Semantics to offer TextDistil, a natural language processing (NLP) pipeline for unstructured data. The integration will allow organizations to transform their text and other unstructured data into a rich set of queryable information, readily integrated into data fabrics and enterprise knowledge graphs. This is particularly valuable for the healthcare industry, which deals largely with unstructured data and has experienced an 878% increase in health data over the last five years. About Fluree Founded in 2016 by Brian Platz and Flip Filipowski, Fluree PBC is headquartered in Winston-Salem, North Carolina. Fluree is pioneering a data-first technology approach with its data management platform.

Read More

BIG DATA MANAGEMENT

Synopsys Launches the Era of Smarter SoC Design with ML-Driven Big Data Analytics Technology

Synopsys | June 03, 2022

Driving greater design productivity by harnessing previously untapped design insights with machine learning technology, Synopsys, Inc. (Nasdaq: SNPS) today announced a critical expansion of its EDA data analytics portfolio with the introduction of Synopsys DesignDash design optimization solution. As a complementary product to Synopsys' market-leading Digital Design Family and Synopsys DSO.ai™, the award-winning AI-driven design-space-optimization solution, Synopsys DesignDash is a comprehensive data-visibility and machine intelligence-guided design optimization solution that enables unmatched productivity in advanced SoC design. The Synopsys DesignDash solution delivers a real-time, unified, 360-degree view of all design activities for faster decision making, a deeper understanding of run-to-run, design-to-design and project-to-project trends, and enhanced collaboration in the SoC development process. "As a leading supplier of SoCs that are powering and transforming numerous high-impact industries, we pride ourselves on being able to push the limits of achievable device performance while also accelerating our customers' time-to-market," said Hiroshi Ikeda, director, Methodology Development Office, Global Development Group at Socionext. "We're very excited by the Synopsys DesignDash analytics solution as a systematic way to capture, consume and evaluate our vast design activity in a scalable way, enabling us to share and transfer expert knowledge across our worldwide design teams to enhance productivity and efficiency." Unlocking the Potential Within Vast Volumes of Digital Design Data The digital design flow holds a wealth of information from myriad sources that, properly utilized, could help teams optimize increasingly complex designs faster. According to Gartner® Inc., "By 2023, overall analytics adoption will increase from 35% to 50%, driven by vertical- and domain-specific augmented analytics solutions."1. The introduction of Synopsys DesignDash is the latest step in a multi-year, multi-disciplinary development effort to address the need for exponential gains in design productivity in the face of massive growth in system complexity, shrinking market windows and an increasingly challenging resource landscape. The cloud-optimized Synopsys DesignDash design optimization solution greatly enhances design productivity by: Providing extensive real-time design status through powerful visualizations and interactive dashboards. Deploying deep analytics and machine learning to extract and reveal actionable understanding from vast volumes of structured and unstructured EDA metrics and tool-flow data. Quickly classifying design trends, identifying design limitations, providing guided root-cause analysis and delivering flow consumable, prescriptive resolutions. With deeper design insights, designers can achieve more effective debug and optimization workflows, realize improved quality of results (QoR) and significantly extend overall design- and project-flow efficiency and effectiveness. This extensive insight and real-time visibility additionally deliver comprehensive resource monitoring and tracking that spans all design activities, enabling more data-driven management and risk mitigation throughout the design process. Synopsys DesignDash is natively integrated with the Synopsys Digital Design family of products for seamless data capture, resulting in insights that further accelerate the path towards design closure. The solution complements the Synopsys SiliconDash product, part of the Synopsys Silicon Lifecycle Management Family, forming a pre-silicon to post-silicon data continuum, maximizing opportunities for valuable data analysis across the complete design-to-silicon lifecycle. "SoC complexity across all application niches continues to rise as more functionality and performance is required. "Through the data analytics and machine learning capabilities of the Synopsys DesignDash technology, engineering teams now have an efficient way to share and utilize valuable insights that would otherwise take hours of manual work to compile or, in some cases, not be accessible." Karl Freund, founder, and principal analyst at Cambrian-AI Research "The semiconductor industry needs a dramatic improvement in design process productivity. Improving the quality and speed of engineering decisions with a comprehensive EDA data analytics platform is a critical step in this direction," said Sanjay Bali, vice president of Marketing and Strategy for the Silicon Realization Group at Synopsys. "Synopsys DesignDash unlocks the potential of the significant and growing volumes of EDA metrics and design-flow data, heralding a new era in smarter IC design by deploying an expanse of advanced data analytics and targeted machine learning to effectively guide design teams to achieve or exceed their product goals and schedules." About Synopsys Synopsys, Inc. is the Silicon to Software™ partner for innovative companies developing the electronic products and software applications we rely on every day. As an S&P 500 company, Synopsys has a long history of being a global leader in electronic design automation (EDA) and semiconductor IP and offers the industry's broadest portfolio of application security testing tools and services. Whether you're a system-on-chip (SoC) designer creating advanced semiconductors, or a software developer writing more secure, high-quality code, Synopsys has the solutions needed to deliver innovative products.

Read More

BUSINESS INTELLIGENCE

BigID launches Data Insights Studio to close the gap between insight and action

BigID | April 08, 2022

BigID, the leading data intelligence platform that enables organizations to know their enterprise data and take action for privacy, security, and governance, today launched Data Insights Studio, a new capability that provides rich and insightful reporting and analytics about the state of data across the entire organization. Data Insights Studio gives privacy, security, and governance teams the power to create rich, insightful, and actionable reporting best suited for their organization and easily monitor relevant metrics to better assess the progress of their data initiatives. Data Insights Studio seeks to close the gap between insight and action so that teams have the speed to make the best decisions about their data. BigID Data Studio enables organizations to know when and where to take action on their data through accurate reporting and analytics. Capabilities include: Driving proactive executive decision-making with actionable insights about data security, privacy, and governance initiatives. Actively monitoring trends, metrics, and important KPIs over time while also allowing for forecastability. Empowering users through self-service, configurable reporting, and alleviating the burden off of IT admins. Centralizing data intelligence holistically for organizations with global data footprints. "Data Insights Studio brings a whole new meaning to data intelligence. We're giving customers the power to visualize their data like never before. We strongly believe that providing easy and customizable reporting of how metadata changes over time and across multiple sites, as well as an ability to analyze trends and monitor critical KPIs, is the key to facilitating and accelerating better data management and value on data across the organization." Nimrod Vax, Co-Founder and Head of Product at BigID Reporting can take on various forms and provides immense value to help illustrate the direction and progress of initiatives. Unfortunately, developing proper executive reporting that addresses the needs of an organization can be nuanced and cumbersome. IT teams are often required to manually create reports and analytics to fit their needs, a method that not only fails to scale well but also lacks proper speed and accuracy to drive the right decisions. Data Insights Studio aims to close the gap between insight and action so that IT teams have the agility to act on their data with certainty. About BigID BigID's data intelligence platform enables organizations to know their enterprise data and take action for privacy, protection, and perspective. Customers deploy BigID to proactively discover, manage, protect, and get more value from their regulated, sensitive, and personal data across their data landscape. BigID has been recognized for its data intelligence innovation as a 2019 World Economic Forum Technology Pioneer, named to the 2021 Forbes Cloud 100, the 2021 Inc 5000 as the #19th fastest growing company and #1 in Security, a Business Insider 2020 AI Startup to Watch, and an RSA Innovation Sandbox winner.

Read More

BIG DATA MANAGEMENT

Fluree Announces Significant Momentum in Digital Trust and Privacy Collaboration, Strategic Partnerships and Developer Adoption, on the Path to Web3

Fluree | December 27, 2021

Fluree, provider of the Web3 data platform, today announced significant momentum as the technology of choice for privacy-preserving data ecosystems. Fluree’s immutable semantic graph database played a key role in a wide range of projects in 2021, including secure academic credentials for projects funded by the Department of Education, a tamper-proof and fair blockchain-backed election, and off-chain data storage for Cardano, the sixth-largest cryptocurrency in the world. “It’s inspiring to see the ways that developers are taking advantage of Fluree’s ability to deliver trust, semantic context and security to data projects,” said Fluree Co-CEO and Co-Founder Brian Platz. “Support for our platform is at an all-time high, driven by data-centric architecture that can power trusted, interoperable data ecosystems.” “Mainstream adoption of Web3 — the decentralized Internet of data — is on the horizon. As the rise of data ecosystems are met with privacy, trust and interoperability challenges, Fluree is uniquely poised to become the infrastructure of choice in the emerging Web3 market,” said Dan Malven, Managing Director at 4490 Ventures. Surge in Developer Adoption: 500% Growth in 2021 Fluree’s open source technology grew 500% in users in 2021, topping 100,000 total downloads to date as it becomes the technology of choice for privacy-preserving data ecosystems. Key use cases in verifiable credentials, education technology, enterprise knowledge graphs, and blockchain applications continue to emerge. Fluree’s recently overhauled developer portal and growing Slack community accommodates the influx in developer adoption, prioritizing the Fluree developer experience and community. Fluree’s rise in both developer adoption and strategic partners has been recognized, winning local awards such as Tech Tribune’s Best Tech Startup in Winston-Salem to being recognized as CRN’s Coolest Database System Company of 2021 as well as a winner of Business Intelligence Group’s Fortress Cyber Security Award. Digital Privacy and Verifiable Credentials for the Public Sector, Supporting Education and Health Care Improvements Verifiable credentials and decentralized identifiers have become a central theme in rising Fluree use cases across education ecosystems and healthcare. As the world begins to understand the value of privacy in digital ecosystems, organizations have chosen Fluree to power solutions that return ownership of information to consumers. Education Credentials: Two winning projects of the American Council of Education’s Blockchain Innovation Challenge, funded by the Department of Education, are using Fluree's technology to transform credentialing in academic ecosystems. The LifeLong Learner Project focuses on providing teachers with a wallet to store and present certifications as they move throughout their careers. The UnBlockED project is focused on creating an open transfer exchange that will empower college students by streamlining transfer credit recognition. In both projects, Fluree’s technology provides the foundation for the exchange of secure and interoperable verifiable credentials across owners, issuers, and third-party institutions. Key partners within these initiatives include the University of Arizona, the Gardner Institute, and Georgia Tech. Healthcare Credentials: Pulse Connect has partnered with Fluree to build verifiable credential solutions for patients and health providers. This will help support verification requirements around vaccine credentialing in view of increasing vaccine mandates. Strategic Partnerships: Supporting Cryptocurrency Advancements, Tamper-Proof Elections and Codifying Unstructured Data Much of Fluree’s 2021 momentum stems from Fluree’s growing partner ecosystem, which recently won the CRN’s “Channel Chiefs Award.” Examples of rising stars in Fluree’s Partner Ecosystem include: Building a Metadata Sidechain Solution for the Sixth Largest Cryptocurrency: The community supporting the high-ranking cryptocurrency blockchain platform Cardano selected Ikigai Technologies and Fluree to power Logosphere. The Logosphere project proposes Fluree as an "off-chain decentralized app (dApp) data storage solution" for the metadata related to Cardano transactions. Instead of placing data into siloed databases, Fluree will act as a secure and interoperable metadata layer for dApp developers. This will enable a new class of data-driven dApps, such as non-fungible token (NFT) exchanges, decentralized knowledge graphs, and other data-centric Web3 applications. Powering the World’s First End-to-End Blockchain Election: Marzex.tech technologies delivered a Fluree-powered digital voting platform for the International Islamic University of Malaysia. The digital platform used Fluree’s backend to successfully register identities, facilitate private voting, and thwart efforts to tamper with the election. Turning Text into Trusted, Interoperable Data: Fluree integrated with Lead Semantics to offer TextDistil, a natural language processing (NLP) pipeline for unstructured data. The integration will allow organizations to transform their text and other unstructured data into a rich set of queryable information, readily integrated into data fabrics and enterprise knowledge graphs. This is particularly valuable for the healthcare industry, which deals largely with unstructured data and has experienced an 878% increase in health data over the last five years. About Fluree Founded in 2016 by Brian Platz and Flip Filipowski, Fluree PBC is headquartered in Winston-Salem, North Carolina. Fluree is pioneering a data-first technology approach with its data management platform.

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