7 Top Data Analytics Trends

Aashish Yadav | March 31, 2022 | 25 views

7 Top Data Analytics Trends

The COVID-19 compelled organizations utilizing traditional analytics methods to accept digital data analytics platforms. The pandemic has also accelerated the digital revolution, and as we already know, data and analytics with technologies like AI, NLP, and ML have become the heart of this digital revolution. Therefore, this is the perfect time to break through data, analytics, and AI to make the most of it and stay a step ahead of competitors. Besides that, Techjury says that by 2023, the big data analytics market is expected to be worth $103 billion. This shows how quickly the field of data analytics is growing.


Today, the data analytics market has numerous tools and strategies evolving rapidly to keep up with the ever-increasing volume of data gathered and used by businesses. Considering the swift pace and increasing use of data analytics, it is crucial to keep upgrading to stay ahead of the curve. But before we explore the leading data analytics trends, let's check out some data analytics use cases.


Data Analytics Use Cases


Customer Relationship Analytics

One of the biggest challenges is recognizing clients who will spend money continuously for a long period purchasing their products. This insight will assist businesses in attracting customers who will add long-term value to their business.


Product Propensity

Product propensity analytics combines data on buying actions and behaviors with online behavioral indicators from social media and e-commerce to give insight into the performance of various campaigns and social media platforms promoting the products and services of your company. This enables your business to forecast which clients are most likely to purchase your products and services and which channels are most likely to reach those customers. This lets you focus on the channels that have the best chance of making a lot of money.


Recommendation Engines

There are recommendations on YouTube, Spotify, Amazon Prime Videos, or other media sites, "recommendations for you." These customized recommendations help users save time and improve their entire customer experience.


Top Data Analytics Trends That Will Shape 2022


1. Data Fabrics Architecture
The goal of data fabric is to design an exemplary architecture and advise on when data should be delivered or changed. Since data technology designs majorly rely on the ability to use, reuse, and mix numerous data integration techniques, the data fabric reduces integration data technology design time by 30%, deployment time by 30%, and maintenance time by 70%.

"The data fabric is the next middleware."

- ex-CTO of Splunk, Todd Papaioannou,

2. Decision Intelligence
Decision intelligence directly incorporates data analytics into the decision process, with feedback loops to refine and fine-tune the process further.

Decision intelligence can be utilized to assist in making decisions, but it also employs techniques like digital twin simulations, reinforcement learning, and artificial intelligence to automate decisions where necessary.

3. XOps
With artificial intelligence (AI) and data analytics throughout any firm, XOps has become an essential aspect of business transformation operations. XOps uses DevOps best practices to improve corporate operations, efficiency, and customer experience. In addition, it wants to make sure that the process is reliable, reusable, and repeatable and that there is less technology and process duplication.

4. Graph Analytics
Gartner predicts that by 2025, 80% of data and analytics innovation will be developed with the help of graphs. Graph analytics uses engaging algorithms to correlate multiple data points scattered across numerous data assets by exploring relationships. The AI graph is the backbone of modern data and analytics with the help of its expandable features and capability to increase user collaboration and machine learning models.

5. Augmented Analytics
Augmented Analytics is another data-trend technology that is gaining prominence. Machine learning, AI, and natural language processing (NLP) are used in augmented analytics to automate data insights for business intelligence, data preparation, discovery, and sharing. The insights provided through augmented analytics help businesses make better decisions. According to Allied Market Research, the worldwide augmented analytics market is expected to reach $29,856 million by 2025.

6. Self-Service Analytics-Low-code and no-code AI
Low-code and no-code digital platforms are speeding up the transition to self-service analytics. Non-technical business users can now access data, get insights, and make faster choices because of these platforms. As a result, self-service analytics boosts response times, business agility, speed-to-market, and decision-making in today's modern world.

7. Privacy-Enhancing Computation
With the amount of sensitive and personal data being gathered, saved, and processed, it has become imperative to protect consumers' privacy. As regulations become strict and customers become more concerned, new ways to protect their privacy are becoming more important.

Privacy-enhancing computing makes sure that value can be extracted from the data with the help of big data analytics without breaking the rules of the game.


3 Ways in Which the C-Suite Can Ensure Enhanced Use of Data Analytics

There are many businesses that fail to realize the benefits of data analytics. Here are some ways the C-suite can ensure enhanced use of data analytics.


Use Data Analytics for Recommendations

Often, the deployment of data analytics is considered a one-time mission instead of an ongoing, interactive process. According to recent McKinsey research, employees are considerably more inclined to data analytics if their leaders actively commit. If the C-suite starts using analytics for decision-making, it will set an example and establish a reliability factor. This shows that when leaders rely on the suggestions and insights of data analytics platforms, rest of the company will follow the C-suite. This will result in broad usage, better success, and higher adoption rates of data analytics.


Establish Data Analytics Mind-Sets

Senior management starting on this path should learn about data analytics to comprehend what's fast becoming possible. Then they can use the question, "Where might data analytics bring quantum leaps in performance?" to promote lasting behavioral changes throughout the business. A senior executive should lead this exercise with the power and influence to encourage action throughout each critical business unit or function.


Use Machine Learning to Automate Decisions

The C-suite is introducing machine learning as they are recognizing its value for various departments and processes in an organization either processing or fraud monitoring. 79% of the executives believe that AI will make their jobs more efficient and manageable. Therefore, C-level executives would make an effort to ensure the rest of the organization follows that mentality. They will have to start by using machine learning to automate time-consuming and repeatable tasks.


Conclusion

From the above-mentioned data analytics trends one can infer that it is no longer only a means to achieve corporate success. In 2022 and beyond, businesses will need to prioritize it as a critical business function, accurately recognizing it as a must-have for long-term success. The future of data analytics will have quality data and technologies like AI at its center.


FAQ


1. What is the difference between data analytics and data analysis?

Scalability is the key distinguishing factor between analytics and analysis. Data analytics is a broad phrase that encompasses all types of data analysis. The evaluation of data is known as data analysis. Data analysis includes data gathering, organization, storage, and analysis techniques and technologies.


2. When is the right time to deploy an analytics strategy?

Data analytics is not a one-time-only activity; it is a continuous process. Companies should not shift their attention from analytics and should utilize it regularly. Usually, once companies realize the potential of analytics to address concerns, they start applying it to various processes.


3. What is platform modernization?

Modernization of legacy platforms refers to leveraging and expanding flexibility by preserving consistency across platforms and tackling IT issues. Modernization of legacy platforms also includes rewriting a legacy system for software development.

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Predictive Analytics: Implementation in Business Processes

Article | January 12, 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. Here are some of the most common benefits of predictive business analytics and an understanding of how is predictive analytics used in business. Fraud Detection In general, various analyzing techniques are merged to analyze data to enhance the accuracy of pattern recognition and discover criminal behavior, thereby reducing the incidence of frequent fraud. With behavioral analytics, you can look at any suspicious behavior and activities that happen on a network in real-time to look for fraud, zero-day breaches, and underlying threats. Enhancing Business Campaigns The predictive analytics process can help you optimize marketing campaigns and promotional events. Predictive designs helps businesses attract, retain, and increase valuable customers by determining their purchase responses and promoting cross-sell opportunities. Minimizing Potential Risk The predictive analytics process helps businesses decide on appropriate steps to avoid or reduce losses. Predictive analytics is revolutionizing risk management by alerting businesses about future developments. For example, credit scores, which financial institutions use to predict defaulters depending on a user's purchasing behavior. How Does Predictive Analytics Help the C-Suite? The C-suite is the final decision maker, so they are the ones who must use predictive analytics the most for insightful decision-making. Let’s look at ways in which predictive analytics can help C-level executives. Predict Customer Behavior Predictive analytics utilizes data to forecast future customer behavior. Customer intent becomes the primary aspect rather than historical transactional data, allowing for hyper-personalized marketing and communications. For example, researchers at China's Renmin University used predictive analytics and machine learning to figure out that data on consumer interests and jobs can predict customer preferences and purchase intent for cars. 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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Embrace Corporate Performance Management to Enhance Your Business

Article | April 29, 2021

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. To make sure that information can be easily integrated, processed, and reported to meet specific standards, a company should build an ICT infrastructure that is easy to use, complete, and appropriate. Synchronization of Objectives Businesses should not depend only on current tactics while neglecting to develop their own. Instead, they should focus on getting their main objectives out in the open so that CPM and all stakeholders are on the same page. Things to Consider While Choosing a CPM Platform Before investing in corporate performance management software, understand your team’s requirements. What manual tasks do they currently execute? What tools will the team require to keep pace with the growth of the company? Here we have mentioned the top three things to consider while choosing a CPM platform for business. Usability You want your employees to be passionate about the platform and its potential; choose an option that will significantly enhance their day-to-day functioning. Involve your team in the process of choosing a platform so they can give their opinion on how easy it is to use. A user-friendly and accessible CPM system will lead to successful training, deployment, and an instant ROI. Integrations with Existing Tools Make sure your new CPM system can integrate with your existing systems. You may want to import data from your ERP system, BI tools, and spreadsheets in real-time to save time and effort by copying and pasting data between applications. Manual data re-entry takes a lot of time and puts data at risk of being missed or entered incorrectly. This integration is crucial if your business utilizes a data warehouse to integrate data from multiple cloud tools. To do more analysis, you can also export data from the CPM platform into models and spreadsheets and presentations and word documents. Value to the Organization The cheapest option is not always the best one for your business. Evaluate the value of the software to the team, leadership, and organization. How can the program improve efficiency, offer accurate business visibility, and assist with data-driven decisions? This is where value is measured. Conclusion Corporate performance management is the framework that connects your organizational objectives with planning, enabling successful strategy implementation. Investing in CPM software will increase a company's efficiency by handling a reasonably straightforward process. When employees are free from tiresome activities, they can be employed for something useful that will contribute to the company's development. “The true measure of the value of any business leader and manager is performance.” – Brian Tracy Frequently Asked Questions What Is the Role of CPM in Business? CPM software, which was earlier used in finance departments, is now meant to be used enterprise-wide, usually complementing business intelligence systems. 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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The Art of Developing a Successful Business Intelligence Strategy

Article | December 21, 2020

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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Katipult | July 06, 2022

Katipult Technology Corp. , a leading Fintech provider of software for powering the exchange of capital in equity and debt markets, announced today that its private placements platform, DealFlow, has been upgraded with the addition of a new enterprise-grade data integration module – DealFlow: DataHub. This module enables users to securely link their backend systems with the DealFlow platform, allowing them to directly populate subscription documents with the latest information from their systems of record. "We're very excited to announce the launch of the DealFlow: DataHub module. Our experience working with investment banks and broker dealers showed us that being able to seamlessly interface with their legacy systems of record is critical for helping them accelerate the pace of digital transformation. DealFlow:DataHub further amplifies the efficiency-boosting capabilities of DealFlow by removing yet another manual step in the private placements process. Not only is scalability improved, but there are also positive knock-on effects on compliance as data integrity and continuity are preserved." Gord Breese, Katipult CEO DealFlow:'s DataHub extracts large volumes of data from the commonly used systems of record in the industry, such as ISM or Dataphile. The data is then streamlined and used to populate the intelligent digital subscription documents that are core to the DealFlow platform. With the addition of DealFlow: DataHub, customers will no longer need to manually input or update the data that will populate the subscription documents. Further, DataHub will also enable single sign-on to the DealFlow platform, allowing users to sign on with their standard enterprise credentials. Katipult's goal with DealFlow is to help institutions unlock the full potential of private placements by streamlining as many processes as possible. DealFlow: DataHub represents yet another step forward in that direction. About Katipult Katipult is a provider of industry leading and award-winning software infrastructure for powering the exchange of capital in equity and debt markets. Our cloud-based platform and solutions digitize investment workflow by eliminating transaction redundancy, strengthening compliance, delighting investors, and accelerating deal flow. Katipult provides unparalleled adaptability for regulatory compliance, asset structure, business model, and localization requirements.

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SingleStore and Intel Collaborate to Deliver Next-Generation Real-Time Data Technology

SingleStore | July 07, 2022

SingleStore, the cloud-native database built for speed, scale and powering real-time data-intensive applications, announced it has been accepted as a Gold Status Partner in Intel’s Disruptor Initiative. The program helps companies push the limits of innovation through technical enablement and multi-channel go-to-market activities. As a result, SingleStore customers will benefit by realizing enhanced database performance and hardware-enhanced security to address real-time data challenges while lowering total cost of ownership (TCO). "SingleStore is excited to join Intel’s prestigious Disruptor Initiative and to work closely with their engineers to optimize the performance of SingleStoreDB on current and future Intel architectures. “This collaboration helps our customers reach new levels of data intensity with real-time analytical and transactional workloads.” Oliver Schabenberger, chief innovation officer at SingleStore In running internal benchmarks fueled by 3rd Gen Intel Xeon Scalable processors with built-in AI accelerators, SingleStore has seen a performance improvement of up to 30%*. In addition, Intel and SingleStore are both members of the Bytecode Alliance, a nonprofit organization dedicated to creating a secure network software foundation, building on standards such as WebAssembly (Wasm) and WebAssembly System Interface. SingleStore recently brought Wasm technology to the database market and has collaborated with Intel to bring this unique optimized technology to market. Arijit Bandyopadhyay, chief technology officer for enterprise analytics and AI and head of strategy for the enterprise and cloud, DCAI group at Intel Corporation, said: “As the demand for all types of data and high intensity data applications increase, encapsulating complex queries with high ingest speed, high concurrency and low latency requirements, we couldn't be more excited about collaborating with SingleStore to deliver the next generation of real-time data technology on AI – to enhance digital customer experience, improve operations and security, plus generate new revenue streams.” The effort with Intel is the latest that SingleStore has recently forged with other industry-leading technology companies. Earlier this year, SingleStore partnered with IBM and SAS to deliver ultra-fast insights to accelerate insights for data-intensive applications and reduce TCO. SingleStore growth continues to accelerate due to its unique ability to address real-time applications, strategic partnerships, and investments from leaders like IBM, HPE, Dell Technologies and now Intel. Users and media see the value of SingleStore, too. SingleStore has been recognized with several industry awards, including San Francisco Business Times Fastest-Growing Private Companies in the Bay Area and the Deloitte Fast 500 awards. SingleStore also was recently recognized when it won in four top-rated categories from verified user review site TrustRadius in May. Christoph Malassa, managing consultant and head of analytics and intelligence solutions at Siemens, said this about SingleStore: “With SingleStore, we no longer look at the database as a limiting factor in our business.” About SingleStore The world’s leading brands rely on data — to make the right business decisions, to deliver exceptional customer experiences and to stay ahead of the competition. This reliance on data brings with it a need for simplicity, speed and scale. SingleStore delivers the world’s fastest distributed SQL database for real-time applications, SingleStoreDB. By combining transactional and analytical workloads, SingleStore eliminates performance bottlenecks and unnecessary data movement to support constantly growing, demanding workloads. Digital giants like Hulu, Uber and Comcast, and many more of the world’s leading SaaS providers choose SingleStore to unleash the power of their data — supercharging exceptional, real-time data experiences for their customers.

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DATA SCIENCE

KNIME Accelerates Data Science Democratization Through Snowflake Collaboration

KNIME | June 10, 2022

KNIME, the open source data science company, today announced a strategic partnership with Snowflake, the Data Cloud company, to democratize access to data analytics across all roles and departments. Understanding data is critical for creating business value. With the global data analytics market worth more than $200 billion, it’s necessary for as many people as possible across roles, departments and industries to have access to analytics in their daily jobs for overall better productivity. “Many of our customers rely on Snowflake to power virtually any data workload at scale, while utilizing KNIME to gain value from that data.” Paul Treichler, VP of global partnerships at KNIME Tarik Dwiek, Snowflake’s head of technology partnerships, added, “In partnership with KNIME, we look to enrich the Snowflake ecosystem with tools that can enable an even greater share of enterprises and both technical and non-technical users of data.” The joint offering means that users can access and manipulate data in Snowflake with a low-/no-code platform at no cost. KNIME Analytics Platform is a fully featured analytics workflow “designer” that can be used in conjunction with Snowflake’s Data Cloud to perform a broad range of analytics tasks from data prep to data science. Users can leverage the drag-and-drop interface to prepare and explore data, rapidly build analytical models, create data apps, and present results in BI tools such as Tableau or Power BI. KNIME is flexible and extensible, giving data experts the freedom to work in their preferred environment. Users can build sophisticated analytic models in its low-code/no-code environment or script custom algorithms in a language of their choice with built-in integrations with R, Python, Java and more. KNIME has a vibrant open source community of users who share their knowledge and expertise in specialized forums. Technical and non-technical teams can make use of this community to leverage pre-built components and workflows to accelerate their time to value and also upskill themselves through comprehensive free training and learning content available from KNIME. Upskilling non-technical teams to use data science and analytics leaves technical teams with greater bandwidth and freedom to concentrate on more complex tasks. Across industries, enterprises can also take advantage of KNIME’s commercial offering. KNIME Server offers a suite of features for automation, governance, production deployment and MLOps. Snowflake working in concert with KNIME Server enables organizations to move beyond pilot projects and build enterprise-scale data solutions that are compliant and accessible across the organization. Lastly, KNIME extends the deployment flexibility of Snowflake to the analytics layer, allowing enterprises to utilize the right resources for a given workload or scenario. “We are excited about the partnership between Snowflake and KNIME," said Ryan Bosshart, CEO of phData, the Snowflake 2021 RSI Partner of the Year and KNIME Elite Partner. “We've been building with both Snowflake and KNIME because we believe in platforms and technology that make it easier for people to build data products, in both business and technical roles. I’m excited to see what new use cases are possible with this combination.” About KNIME KNIME helps individuals and organizations make sense of data. KNIME software bridges the worlds of dashboards and advanced analytics through an intuitive interface, appropriate for anybody working with data. It empowers more business experts to be self-sufficient and more data experts to push the business to the bleeding edge of modern data science, integrating the latest AI and machine learning techniques. KNIME is distinct in its open approach, which ensures easy adoption and future-proof access to new technologies.

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BIG DATA MANAGEMENT

Katipult Launches Enterprise-Grade Data Integration Capabilities to its DealFlow Platform

Katipult | July 06, 2022

Katipult Technology Corp. , a leading Fintech provider of software for powering the exchange of capital in equity and debt markets, announced today that its private placements platform, DealFlow, has been upgraded with the addition of a new enterprise-grade data integration module – DealFlow: DataHub. This module enables users to securely link their backend systems with the DealFlow platform, allowing them to directly populate subscription documents with the latest information from their systems of record. "We're very excited to announce the launch of the DealFlow: DataHub module. Our experience working with investment banks and broker dealers showed us that being able to seamlessly interface with their legacy systems of record is critical for helping them accelerate the pace of digital transformation. DealFlow:DataHub further amplifies the efficiency-boosting capabilities of DealFlow by removing yet another manual step in the private placements process. Not only is scalability improved, but there are also positive knock-on effects on compliance as data integrity and continuity are preserved." Gord Breese, Katipult CEO DealFlow:'s DataHub extracts large volumes of data from the commonly used systems of record in the industry, such as ISM or Dataphile. The data is then streamlined and used to populate the intelligent digital subscription documents that are core to the DealFlow platform. With the addition of DealFlow: DataHub, customers will no longer need to manually input or update the data that will populate the subscription documents. Further, DataHub will also enable single sign-on to the DealFlow platform, allowing users to sign on with their standard enterprise credentials. Katipult's goal with DealFlow is to help institutions unlock the full potential of private placements by streamlining as many processes as possible. DealFlow: DataHub represents yet another step forward in that direction. About Katipult Katipult is a provider of industry leading and award-winning software infrastructure for powering the exchange of capital in equity and debt markets. Our cloud-based platform and solutions digitize investment workflow by eliminating transaction redundancy, strengthening compliance, delighting investors, and accelerating deal flow. Katipult provides unparalleled adaptability for regulatory compliance, asset structure, business model, and localization requirements.

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BIG DATA MANAGEMENT

SingleStore and Intel Collaborate to Deliver Next-Generation Real-Time Data Technology

SingleStore | July 07, 2022

SingleStore, the cloud-native database built for speed, scale and powering real-time data-intensive applications, announced it has been accepted as a Gold Status Partner in Intel’s Disruptor Initiative. The program helps companies push the limits of innovation through technical enablement and multi-channel go-to-market activities. As a result, SingleStore customers will benefit by realizing enhanced database performance and hardware-enhanced security to address real-time data challenges while lowering total cost of ownership (TCO). "SingleStore is excited to join Intel’s prestigious Disruptor Initiative and to work closely with their engineers to optimize the performance of SingleStoreDB on current and future Intel architectures. “This collaboration helps our customers reach new levels of data intensity with real-time analytical and transactional workloads.” Oliver Schabenberger, chief innovation officer at SingleStore In running internal benchmarks fueled by 3rd Gen Intel Xeon Scalable processors with built-in AI accelerators, SingleStore has seen a performance improvement of up to 30%*. In addition, Intel and SingleStore are both members of the Bytecode Alliance, a nonprofit organization dedicated to creating a secure network software foundation, building on standards such as WebAssembly (Wasm) and WebAssembly System Interface. SingleStore recently brought Wasm technology to the database market and has collaborated with Intel to bring this unique optimized technology to market. Arijit Bandyopadhyay, chief technology officer for enterprise analytics and AI and head of strategy for the enterprise and cloud, DCAI group at Intel Corporation, said: “As the demand for all types of data and high intensity data applications increase, encapsulating complex queries with high ingest speed, high concurrency and low latency requirements, we couldn't be more excited about collaborating with SingleStore to deliver the next generation of real-time data technology on AI – to enhance digital customer experience, improve operations and security, plus generate new revenue streams.” The effort with Intel is the latest that SingleStore has recently forged with other industry-leading technology companies. Earlier this year, SingleStore partnered with IBM and SAS to deliver ultra-fast insights to accelerate insights for data-intensive applications and reduce TCO. SingleStore growth continues to accelerate due to its unique ability to address real-time applications, strategic partnerships, and investments from leaders like IBM, HPE, Dell Technologies and now Intel. Users and media see the value of SingleStore, too. SingleStore has been recognized with several industry awards, including San Francisco Business Times Fastest-Growing Private Companies in the Bay Area and the Deloitte Fast 500 awards. SingleStore also was recently recognized when it won in four top-rated categories from verified user review site TrustRadius in May. Christoph Malassa, managing consultant and head of analytics and intelligence solutions at Siemens, said this about SingleStore: “With SingleStore, we no longer look at the database as a limiting factor in our business.” About SingleStore The world’s leading brands rely on data — to make the right business decisions, to deliver exceptional customer experiences and to stay ahead of the competition. This reliance on data brings with it a need for simplicity, speed and scale. SingleStore delivers the world’s fastest distributed SQL database for real-time applications, SingleStoreDB. By combining transactional and analytical workloads, SingleStore eliminates performance bottlenecks and unnecessary data movement to support constantly growing, demanding workloads. Digital giants like Hulu, Uber and Comcast, and many more of the world’s leading SaaS providers choose SingleStore to unleash the power of their data — supercharging exceptional, real-time data experiences for their customers.

Read More

DATA SCIENCE

KNIME Accelerates Data Science Democratization Through Snowflake Collaboration

KNIME | June 10, 2022

KNIME, the open source data science company, today announced a strategic partnership with Snowflake, the Data Cloud company, to democratize access to data analytics across all roles and departments. Understanding data is critical for creating business value. With the global data analytics market worth more than $200 billion, it’s necessary for as many people as possible across roles, departments and industries to have access to analytics in their daily jobs for overall better productivity. “Many of our customers rely on Snowflake to power virtually any data workload at scale, while utilizing KNIME to gain value from that data.” Paul Treichler, VP of global partnerships at KNIME Tarik Dwiek, Snowflake’s head of technology partnerships, added, “In partnership with KNIME, we look to enrich the Snowflake ecosystem with tools that can enable an even greater share of enterprises and both technical and non-technical users of data.” The joint offering means that users can access and manipulate data in Snowflake with a low-/no-code platform at no cost. KNIME Analytics Platform is a fully featured analytics workflow “designer” that can be used in conjunction with Snowflake’s Data Cloud to perform a broad range of analytics tasks from data prep to data science. Users can leverage the drag-and-drop interface to prepare and explore data, rapidly build analytical models, create data apps, and present results in BI tools such as Tableau or Power BI. KNIME is flexible and extensible, giving data experts the freedom to work in their preferred environment. Users can build sophisticated analytic models in its low-code/no-code environment or script custom algorithms in a language of their choice with built-in integrations with R, Python, Java and more. KNIME has a vibrant open source community of users who share their knowledge and expertise in specialized forums. Technical and non-technical teams can make use of this community to leverage pre-built components and workflows to accelerate their time to value and also upskill themselves through comprehensive free training and learning content available from KNIME. Upskilling non-technical teams to use data science and analytics leaves technical teams with greater bandwidth and freedom to concentrate on more complex tasks. Across industries, enterprises can also take advantage of KNIME’s commercial offering. KNIME Server offers a suite of features for automation, governance, production deployment and MLOps. Snowflake working in concert with KNIME Server enables organizations to move beyond pilot projects and build enterprise-scale data solutions that are compliant and accessible across the organization. Lastly, KNIME extends the deployment flexibility of Snowflake to the analytics layer, allowing enterprises to utilize the right resources for a given workload or scenario. “We are excited about the partnership between Snowflake and KNIME," said Ryan Bosshart, CEO of phData, the Snowflake 2021 RSI Partner of the Year and KNIME Elite Partner. “We've been building with both Snowflake and KNIME because we believe in platforms and technology that make it easier for people to build data products, in both business and technical roles. I’m excited to see what new use cases are possible with this combination.” About KNIME KNIME helps individuals and organizations make sense of data. KNIME software bridges the worlds of dashboards and advanced analytics through an intuitive interface, appropriate for anybody working with data. It empowers more business experts to be self-sufficient and more data experts to push the business to the bleeding edge of modern data science, integrating the latest AI and machine learning techniques. KNIME is distinct in its open approach, which ensures easy adoption and future-proof access to new technologies.

Read More

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