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Know the Text Analytics Use Cases in Businesses

“Text analytics can help organizations discover patterns in large unstructured data sets. Unstructured data, such as videos, photos, and audio accounts for at least 80% of your company’s data, a true blind spot for most businesses.”

- IBM

Data scientists use advanced data science approaches to examine text. This textual data provides a better understanding of client attitudes toward certain topics or uncovers additional information.

Using this text analytics, you can turn free-form text into structured data for use in prediction models or uncover hidden patterns in your data. If you want, you can use text analysis to identify prospective customers who might be interested in cross-selling, forecast customer attitudes, and understand fraud-prevention behaviors.

Businesses understand the value of their raw text across all industries. As a result, with the help of data, they can reduce operational expenses, find previously unknown linkages, and get a better insight into the future trends.

Is it hard to comprehend that text accounts for 80% of all corporate data?

Online reviews, call center transcripts, consumer surveys, and other written documents are examples. This raw text data is a gold mine for understanding customer attitudes. Text mining and analytics transform these underutilized data sources into actionable information. However, each organization must have the expertise, infrastructure, and analytical perspective to implement this cutting-edge technology in their own way.


How is Text Analytics Used in Companies?

Companies can use NLP and untapped data sources in a number of ground-breaking ways.

Many businesses are already successfully employing text to drive their operations. In addition, text analytics can help you improve your procedures if you're transitioning from business intelligence reporting to data science.


Best Five Text Analytics Use Cases for Businesses

Companies and people, regardless of industry, desire to make better-informed business decisions based on trackable and measurable data. Thanks to improvements in text analysis, companies can now mine the text for insights and improve their service or offering to thrive in their industry.

Read on to understand some of the text analytics use cases that could be applied in your company.


Voice of the Customer (VOC) to Extract Customer Opinion on a product


Companies employ VOC applications to determine what customers say about a product or service.

Emails, call center logs, surveys, and social media streams such as blogs, tweets, forum postings, newsfeeds, and so on are examples of data sources. A telecommunications company, for example, might use voice of customer text analysis to look for complaints about their online services on Twitter.

It will give them an early warning when customers aren’t happy with the service's performance, so that they can act before the client calls to complain or publicly ask for the contract to be terminated.


Lead Generation through Social Media

A piece of social media information can be used to retain and get new clients. It is like the use of the VOC application.

For example, if a person tweets that they are interested in a particular product or service, text analytics can detect this and pass the information to a sales representative, who can then pursue the prospect and turn them into a customer.


Finding Out What Customers Value through Market Research

According to numerous statistics, consumers are interested in other people's thoughts and experiences. According to a study, at least 90% of humans are influenced by what they read.

Also, if the review is terrible, the sentiment is shared. In the last few years, several websites have been collecting reviews of local eateries, vacation spots, and, of course, commercial products.

If your company is thinking about going into a new market or looking into new product ideas, why not start by looking into online market research reviews from real people?

Market research helps you know what features are important to customers when you start your marketing effort. It's critical to know which characteristics influence purchasing decisions and contribute to customer unhappiness.


Use Customer Complaints to Identify New Product Ideals

Understanding the consumer experience is critical, and internet reviews offer a dependable means to do it. Of course, when a consumer encounters problems, no one expects them to be happy, but it can be positive if the support is speedy and helpful.

Social media handles could be effectively used to understand the feedback and complaints of customers. Responding to them promptly makes the customers feel good. It also, gives an idea of the expectations of the customers and the new product ideals.


Analyzing the Customer Sentiments

Whether you're selling a handbag or consumer software on the App Store, text analytics may help you categorize reviews quickly. Unfortunately, a spreadsheet and hours of reading and categorizing reviews are generally required for the manual option. Aside from the discomfort of working long hours, we frequently find irregularities due to the physical nature of this labor. So why not create a data categorization and scoring model that you can use to rerun the data daily, weekly, or monthly?


Summing Up

Companies now have many options to perform text analysis thanks to the rise and availability of unstructured text data. However, simply wanting to use text analytics and predictive analytics isn't enough. You need to first understand where you are as a company from an analytical point of view, and then you need to create a plan on how to embrace these new opportunities. Understanding where you are now can help you determine your next steps and protect you from taking on more than you can handle.


Frequently Asked Questions


How do companies use text analytics?

Text analytics is being used by businesses to analyze consumer comments, evaluate client interactions, assess claims, and uncover compliance concerns. Text analytics software based on natural language processing (NLP) can be used to quickly scan internal legal documents for words and phrases related to finance or fraud.


What can text analytics be used for?

Text analytics is used to gain deeper insights from unstructured text. For example, it can help you see a pattern or trend.


Can business intelligence be improved through text analytics?

Text analytics can help you understand trends, patterns, and actionable insights that you can apply to make data-driven decisions. It can be done by combining the findings of text analysis with business intelligence tools to put the numbers into easy-to-understand reports and images.

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CORDA Technologies Inc

Corda Technologies is the leading provider of enterprise solutions for creating dashboards and interactive data visualization solutions that enhance performance management and smart decision-making. For a decade, Corda has led the evolution of data visualization from static charts and graphs to interactive, intuitive strategic dashboards. Its award-winning solutions include developer tools, enterprise server products and professional services that improve business performance and enable customers worldwide to enhance bottom-line results.

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Re-prioritizing how you spend your time, how you build out your team and the resources you invest in channels and efforts are critical steps to achieving marketing team success" } },{ "@type": "Question", "name": "What is the use of marketing analytics?", "acceptedAnswer": { "@type": "Answer", "text": "Marketing analytics is used to measure how well your marketing efforts are performing and to determine what can be done differently to get better results across marketing channels." } },{ "@type": "Question", "name": "Which companies use marketing analytics?", "acceptedAnswer": { "@type": "Answer", "text": "Marketing analytics enables you to improve your overall marketing program performance by identifying channel deficiencies, adjusting strategies and tactics as needed, optimizing processes, etc. Companies like Netflix, Sephora, EasyJet, and Spotify use marketing analytics to improve their markeitng performance as well." } }] }

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The industries listed below have established themselves and are now at par with companies that are already reaping benefits from BI tools on a regular basis. E-commerce E-commerce is one industry that has greatly benefited from business intelligence tools and techniques. To improve their supply chain, e-commerce giants like Amazon must constantly monitor and analyze data. Amazon, in particular, has a huge supply chain that involves 11 marketplaces and sells over 3 billion products. Retail Business intelligence is used by players in the retail industry to help them recognize and target potential consumers and strengthen their relations with existing customers. Retail businesses can use business intelligence tools to combine data from CRMs, ERPs, and other systems to get a comprehensive, and clear idea of their consumers. Entertainment Today, companies in the media and entertainment industries help you narrow down your search for TV shows, movies, music, and other media by making intelligent suggestions. Business intelligence is used by media streaming giants like Netflix and Spotify to generate a list of recommended movies, shows, and songs based on the customer's preferences and streaming history. Top Business Intelligence Tools Choosing the best business intelligence tools is a personal decision based on your company's requirements. Are you looking for a business intelligence tool that lets you make interactive data visualizations or a tool that lets you do in-depth financial data analysis? While each business's requirements are different and unique, there are several business intelligence tools that work well across a wide range of businesses and industries. Here we have made a list of business intelligence tools named in Gartner’s Magic Quadrants 2021. Board Board International is made up of three tools, which work together. They are business intelligence, predictive analytics, and performance management. Domo Domo is a cloud-based platform that is easy to use and focuses on business-user-deployment dashboards. Microsoft Power BI Microsoft Power BI is one of the most popular BI tools available in the market. It’s easy for clients to use the Power BI app to analyze and visualize data from local or cloud sources, publishing their reports to the Power BI platform. Oracle Analytics Cloud Conversational analytics can be used in the Oracle analytics cloud to answer questions in natural language. It can also automatically generate natural language explanations to help people understand visualizations and trends. SAS Visual Analytics The SAS Visual Analytics tool aims to highlight critical correlations in datasets. In the new edition, there are automated suggestions for relevant factors, as well as visualizations and insights from natural language. Conclusion These business intelligence tools can help with a wide range of tasks inside a company. Off-the-shelf technologies necessarily focus on wide appeal instead of specialized features, since a single tool cannot accomplish all the task. There are several types of BI tools available on the market; businesses can explore and test them before making a final choice on which one to incorporate. Business intelligence is a flexible and effective tool that can be used in almost every industry. FAQ Will BI systems integrate with existing systems? Providers of business intelligence solutions understand the need to integrate data from many platforms. To connect directly with the existing systems and databases, they require a multitude of specialized drivers. Every new business intelligence system version adds to the list of accessible drivers. Is there a need to modify existing IT systems to integrate them with BI tools? The implementation of a BI system does not require the intervention of any existing systems. Some systems need more configuration to connect them to business intelligence tools. What is the time frame required to implement a business intelligence system? It depends on the scope of the project. Implementing business intelligence tools might take anywhere from a few weeks to several months. Many companies begin to see the benefits and decide to expand their system by adding new areas and features.

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Big Data Management, Data Visualization, Data Architecture

Data Virtualization: A Dive into the Virtual Data Lake

Article | August 18, 2022

When it comes to marketing today, big data analytics has become a powerful being. The raw material marketers need to make sense of the information they are presented with so they can do their jobs with accuracy and excellence. Big data is what empowers marketers to understand their customers based on any online action they take. Thanks to the boom of big data, marketers have learned more about new marketing trends and preferences, and behaviors of the consumer. For example, marketers know what their customers are streaming to what groceries they are ordering, thanks to big data. Data is readily available in abundance due to digital technology. Data is created through mobile phones, social media, digital ads, weblogs, electronic devices, and sensors attached through the internet of things (IoT). Data analytics helps organizations discover newer markets, learn how new customers interact with online ads, and draw conclusions and effects of new strategies. Newer sophisticated marketing analytics software and analytics tools are now being used to determine consumers’ buying patterns and key influencers in decision-making and validate data marketing approaches that yield the best results. With the integration of product management with data science, real-time data capture, and analytics, big data analytics is helping companies increase sales and improve the customer experience. In this article, we will examine how big data analytics are transforming the marketing industry. Personalized Marketing Personalized Marketing has taken an essential place in direct marketing to the consumers. Greeting consumers with their first name whenever they visit the website, sending them promotional emails of their favorite products, or notifying them with personalized recipes based on their grocery shopping are some of the examples of data-driven marketing. When marketers collect critical data marketing pieces about customers at different marketing touchpoints such as their interests, their name, what they like to listen to, what they order most, what they’d like to hear about, and who they want to hear from, this enables marketers to plan their campaigns strategically. Marketers aim for churn prevention and onboarding new customers. With customer’s marketing touchpoints, these insights can be used to improve acquisition rates, drive brand loyalty, increase revenue per customer, and improve the effectiveness of products and services. With these data marketing touchpoints, marketers can build an ideal customer profile. Furthermore, these customer profiles can help them strategize and execute personalized campaigns accordingly. Predictive Analytics Customer behavior can be traced by historical data, which is the best way to predict how customers would behave in the future. It allows companies to correctly predict which customers are interested in their products at the right time and place. Predictive analytics applies data mining, statistical techniques, machine learning, and artificial intelligence for data analysis and predict the customer’s future behavior and activities. Take an example of an online grocery store. If a customer tends to buy healthy and sugar-free snacks from the store now, they will keep buying it in the future too. This predictable behavior from the customer makes it easy for brands to capitalize on that and has been made easy by analytics tools. They can automate their sales and target the said customer. What they would be doing gives the customer chances to make “repeat purchases” based on their predictive behavior. Marketers can also suggest customers purchase products related to those repeat purchases to get them on board with new products. Customer Segmentation Customer segmentation means dividing your customers into strata to identify a specific pattern. For example, customers from a particular city may buy your products more than others, or customers from a certain age demographic prefer some products more than other age demographics. Specific marketing analytics software can help you segment your audience. For example, you can gather data like specific interests, how many times they have visited a place, unique preferences, and demographics such as age, gender, work, and home location. These insights are a golden opportunity for marketers to create bold campaigns optimizing their return on investment. They can cluster customers into specific groups and target these segments with highly relevant data marketing campaigns. The main goal of customer segmentation is to identify any interesting information that can help them increase revenue and meet their goals. Effective customer segmentation can help marketers with: • Identifying most profitable and least profitable customers • Building loyal relationships • Predicting customer patterns • Pricing products accordingly • Developing products based on their interests Businesses continue to invest in collecting high-quality data for perfect customer segmentation, which results in successful efforts. Optimized Ad Campaigns Customers’ social media data like Facebook, LinkedIn, and Twitter makes it easier for marketers to create customized ad campaigns on a larger scale. This means that they can create specific ad campaigns for particular groups and successfully execute an ad campaign. Big data also makes it easier for marketers to run ‘remarketing’ campaigns. Remarketing campaigns ads follow your customers online, wherever they browse, once they have visited your website. Execution of an online ad campaign makes all the difference in its success. Chasing customers with paid ads can work as an effective strategy if executed well. According to the rule 7, prospective customers need to be exposed to an ad minimum of seven times before they make any move on it. When creating online ad campaigns, do keep one thing in mind. Your customers should not feel as if they are being stalked when you make any remarketing campaigns. Space out your ads and their exposure, so they appear naturally rather than coming on as pushy. Consumer Impact Advancements in data science have vastly impacted consumers. Every move they make online is saved and measured. In addition, websites now use cookies to store consumer data, so whenever these consumers visit these websites, product lists based on their shopping habits pop up on the site. Search engines and social media data enhance this. This data can be used to analyze their behavior patterns and market to them accordingly. The information gained from search engines and social media can be used to influence consumers into staying loyal and help their businesses benefit from the same. These implications can be frightening, like seeing personalized ads crop up on their Facebook page or search engine. However, when consumer data is so openly available to marketers, they need to use it wisely and safeguard it from falling into the wrong hands. Fortunately, businesses are taking note and making sure that this information remains secure. Conclusion The future of marketing because of big data and analytics seems bright and optimistic. Businesses are collecting high-quality data in real-time and analyzing it with the help of machine learning and AI; the marketing world seems to be up for massive changes. Analytics are transforming marketing industry to a different level. And with sophisticated marketers behind the wheel, the sky is the only limit. Frequently Asked Questions Why is marketing analytics so important these days? Marketing analytics helps us see how everything plays off each other, and decide how we might want to invest moving forward. Re-prioritizing how you spend your time, how you build out your team, and the resources you invest in channels and efforts are critical steps to achieving marketing team success. What is the use of marketing analytics? Marketing analytics is used to measure how well your marketing efforts are performing and to determine what can be done differently to get better results across marketing channels. Which companies use marketing analytics? Marketing analytics enables you to improve your overall marketing program performance by identifying channel deficiencies, adjusting strategies and tactics as needed, optimizing processes, etc. Companies like Netflix, Sephora, EasyJet, and Spotify use marketing analytics to improve their markeitng performance as well. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "Why is marketing analytics so important these days?", "acceptedAnswer": { "@type": "Answer", "text": "Marketing analytics helps us see how everything plays off each other, and decide how we might want to invest moving forward. Re-prioritizing how you spend your time, how you build out your team and the resources you invest in channels and efforts are critical steps to achieving marketing team success" } },{ "@type": "Question", "name": "What is the use of marketing analytics?", "acceptedAnswer": { "@type": "Answer", "text": "Marketing analytics is used to measure how well your marketing efforts are performing and to determine what can be done differently to get better results across marketing channels." } },{ "@type": "Question", "name": "Which companies use marketing analytics?", "acceptedAnswer": { "@type": "Answer", "text": "Marketing analytics enables you to improve your overall marketing program performance by identifying channel deficiencies, adjusting strategies and tactics as needed, optimizing processes, etc. Companies like Netflix, Sephora, EasyJet, and Spotify use marketing analytics to improve their markeitng performance as well." } }] }

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Data Architecture

Enhance Your Business with Data Modeling Techniques

Article | January 24, 2022

Big Data has grown more valuable, helping businesses grow with features like real-time insights and enhanced decision-making; investing in a data strategy helps to stay ahead of the competition. Contents 1. Introduction 2. Leveraging Big Data for Competitive Edge and Sales Growth 3. Benefits of Big Data Analytics in Businesses 3.1 Improved Customer Insights 3.2 Enhanced Operational Efficiency 3.3 Better Decision-Making 3.4 New Product Development 3.5 Competitive Intelligence and Market Research 4. The Path Ahead 1. Introduction The benefits of big data for organizations have amplified with the advent of digital transformation and the prevalence of cloud technology, the Internet of Things (IoT), and ubiquitous internet access. A comprehensive data strategy has become a prerequisite for organizations to retain their competitive edge and leverage big data's advantages. Data analytics is widely employed across different industries and departments, including finance, human resources, and online retail, to glean insights into customer behavior and identify fraudulent activities. In addition, big data in business assumes a critical role in furthering social good by facilitating the monitoring of emissions and pollutants, aiding against climate change. 2. Leveraging Big Data for Competitive Edge and Sales Growth Big data is vital for companies seeking to gain a competitive edge and foster innovation in the current business landscape. By leveraging big data, companies can quickly extract valuable insights from vast amounts of data. This requires investments in tools & technologies, and skilled data analysts & scientists. With a robust big data strategy in place, companies optimize operations, identify new opportunities, and drive innovation. Furthermore, data analytics plays a crucial role in boosting sales by providing insights into customer behavior, preferences, and buying patterns. Companies can optimize their marketing, pricing, and product placement strategies through data analysis, thus leading to increased revenue. Real-time data enables businesses to adapt to market changes quickly, improving their agility and competitiveness. Therefore, developing data analytics capabilities is imperative for businesses to stay ahead and gain a competitive edge. 3. Benefits of Big Data Analytics in Businesses 3.1 Improved Customer Insights Big data has revolutionized how businesses gain a competitive edge through data analytics, offering improved customer insights by analyzing their behavior, preferences, and sentiment toward products. As a result, companies personalize experiences, segment audiences, map customer journeys, and enhance satisfaction. By analyzing data from multiple sources, companies create a 360-degree view of their customers and offer targeted marketing campaigns. 3.2 Enhanced Operational Efficiency Big data improves operational efficiency through predictive maintenance, supply chain optimization, and fraud detection. Predictive maintenance reduces downtime and increases productivity by identifying potential equipment failures. Supply chain optimization streamlines logistics processes, reducing shipping times and costs. Fraud detection identifies and prevents fraudulent activities, protecting businesses from financial losses. 3.3 Better Decision-Making Data-driven decision-making is one of the benefits of using big data, as it provides real-time insights into market trends, customer preferences, and key performance indicators. This helps companies make informed decisions to drive growth and success. Additionally, big data improves decision-making by providing real-time analytics for risk assessment and management, allowing businesses to identify and mitigate potential risks before they become major issues. 3.4 New Product Development Big data uses in businesses enable creation of innovative products and services by analyzing customer feedback and market trends. By gaining insights into customer needs and preferences, businesses identify new opportunities and optimize & innovate their products. 3.5 Competitive Intelligence and Market Research Big data is helpful in providing competitive intelligence and market research. Social listening is a way for businesses to use big data to gain insights into customer sentiment, preferences, and behavior. By analyzing conversations on social media, companies can identify areas for improvement and create effective marketing campaigns. Competitor analysis is another crucial use case for big data in business. By analyzing data on competitors' strategies, businesses can adjust their own strategies and gain a competitive edge. For example, companies can optimize their offerings by tracking competitors' pricing strategies, marketing tactics, and product offerings. 4. The Path Ahead With the continuous evolution of technology, the benefits of big data in business have become increasingly significant in day-to-day operations. The proliferation of digital transformation has provided companies with access to an overwhelming amount of data. In order to maintain a competitive edge, it is imperative for organizations to establish a comprehensive data strategy. However, merely collecting data is insufficient to leverage the potential of big data fully. Companies must possess the necessary tools and expertise to analyze and interpret it. This necessitates investment in advanced analytics tools, as well as the recruitment of data scientists and analysts who can extract valuable insights from the data.

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Data Science

7 Top Data Analytics Trends

Article | March 31, 2022

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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CORDA Technologies Inc

Corda Technologies is the leading provider of enterprise solutions for creating dashboards and interactive data visualization solutions that enhance performance management and smart decision-making. For a decade, Corda has led the evolution of data visualization from static charts and graphs to interactive, intuitive strategic dashboards. Its award-winning solutions include developer tools, enterprise server products and professional services that improve business performance and enable customers worldwide to enhance bottom-line results.

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Big Data Management

NetApp Empowers Secure Cloud Sovereignty with StorageGRID

NetApp | November 08, 2023

NetApp introduces StorageGRID for VMware Sovereign Cloud, enhancing data storage and security for sovereign cloud customers. NetApp's Object Storage plugin for VMware Cloud Director enables seamless integration of StorageGRID for secure Object Storage for unstructured data. NetApp's Sovereign Cloud integration ensures data sovereignty, security, and data value while adhering to regulatory standards. NetApp, a prominent global cloud-led, data-centric software company, has recently introduced NetApp StorageGRID for VMware Sovereign Cloud. This NetApp plugin offering for VMware Cloud Director Object Storage Extension empowers sovereign cloud customers to cost-efficiently secure, store, protect, and preserve unstructured data while adhering to global data privacy and residency regulations. Additionally, NetApp has also unveiled the latest release of NetApp ONTAP Tools for VMware vSphere (OTV 10.0), which is designed to streamline and centralize enterprise data management within multi-tenant vSphere environments. The concept of sovereignty has emerged as a vital facet of cloud computing for entities that handle highly sensitive data, including national and state governments, as well as tightly regulated sectors like finance and healthcare. In this context, national governments are increasingly exploring ways to enhance their digital economic capabilities and reduce their reliance on multinational corporations for cloud services. NetApp's newly introduced Object Storage plugin for VMware Cloud Director offers Cloud Service Providers a seamless means to integrate StorageGRID as their primary Object Storage solution to provide secure Object Storage for unstructured data to their customers. This integration provides StorageGRID services into the familiar VMware Cloud Director user interface, thereby minimizing training requirements and accelerating time to revenue for partners. A noteworthy feature of StorageGRID is its universal compatibility and native support for industry-standard APIs, such as the Amazon S3 API, facilitating smooth interoperability across diverse cloud environments. Enhanced functionalities like automated lifecycle management further ensure cost-effective data protection, storage, and high availability for unstructured data within VMware environments. The integration of NetApp's Sovereign Cloud with Cloud Director empowers providers to offer customers: Robust assurance that sensitive data, including metadata, remains under sovereign control, safeguarding against potential access by foreign authorities that may infringe upon data privacy laws. Heightened security and compliance measures that protect applications and data from evolving cybersecurity threats, all while maintaining continuous compliance with infrastructure, trusted local, established frameworks, and local experts. A future-proof infrastructure capable of swiftly reacting to evolving data privacy regulations, security challenges, and geopolitical dynamics. The ability to unlock the value of data through secure data sharing and analysis, fostering innovation without compromising privacy laws and ensuring data integrity to derive accurate insights. VMware Sovereign Cloud providers are dedicated to designing and operating cloud solutions rooted in modern, software-defined architectures that embody the core principles and best practices outlined in the VMware Sovereign Cloud framework. Workloads within VMware Sovereign Cloud environments are often characterized by a diverse range of data sets, including transactional workloads and substantial volumes of unstructured data, all requiring cost-effective and integrated management that is compliant with regulated standards for sovereign and regulated customers. In addition to the aforementioned advancements, NetApp also announced a collaborative effort with VMware aimed at modernizing API integrations between NetApp ONTAP and VMware vSphere. This integration empowers VMware administrators to streamline the management and operations of NetApp ONTAP-based data management platforms within multi-tenant vSphere environments, all while allowing users to leverage a new micro-services-based architecture that offers enhanced scalability and availability. With the latest releases of NetApp ONTAP and ONTAP Tools for vSphere, NetApp has significantly made protection, provisioning, and securing modern VMware environments at scale faster and easier, all while maintaining a centralized point of visibility and control through vSphere. NetApp ONTAP Tools for VMware provides two key benefits to customers: A redefined architecture featuring VMware vSphere APIs for Storage Awareness (VASA) integration, simplifying policy-driven operations and enabling cloud-like scalability. An automation-enabled framework driven by an API-first approach, allowing IT teams to seamlessly integrate with existing tools and construct end-to-end workflows for easy consumption of features and capabilities.

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Big Data Management

Google Cloud and Bloomberg Unite to Accelerate Customers Data Strategies

Bloomberg | November 06, 2023

Bloomberg and Google Cloud integrate Data License Plus (DL+) with BigQuery for efficient data access and analytics. Customers can access fully modeled data within BigQuery, eliminating data preparation time. Mackenzie Investments adopts DL+ ESG Manager to host the acquisition, management, and publishing of Multi-vendor ESG data. Bloomberg has unveiled a new offering designed to accelerate the data strategies of Google Cloud customers by integrating Bloomberg's cloud-based data management solution, Data License Plus (DL+), with Google Cloud's fully managed, serverless data warehouse, BigQuery. Now, with access to Bloomberg's extensive experience modeling, managing, and delivering vast quantities of complex content, mutual customers can receive their Bloomberg Data License (DL) data, entirely modeled and seamlessly combined within BigQuery. As a result, organizations can leverage the advanced analytics capabilities of Google Cloud to extract more value from critical business information quickly and efficiently with minimal data wrangling. Through this extended collaboration, customers can harness the powerful analytics features of BigQuery and tap into Bloomberg's extensive collection of datasets available through Data License to power their most essential workloads. Bloomberg's Data License content offers a wide variety, including reference, pricing, ESG, regulatory, estimates, fundamentals, and historical data, supporting operational, quantitative, and investment research workflows, covering over 70 million securities and 40,000 data fields. Key benefits include: Direct Access to Bloomberg Data in BigQuery: Bloomberg customers can seamlessly access Bloomberg Data License content within BigQuery, allowing for scalable use across their organization. This eliminates the time-consuming tasks of ingesting and structuring third-party datasets, thereby accelerating the time-to-value for analytics projects. Elimination of Data Barriers: Google Cloud and Bloomberg will make Bloomberg's DL+ solution available to mutual customers via BigQuery. This allows for the delivery of fully modeled Bloomberg data and multi-vendor ESG content within their analytics workloads. In a recent announcement, Bloomberg revealed that Mackenzie Investments has selected DL+ ESG Manager to host the acquisition, management, and publishing of multi-vendor ESG data. This move positions Mackenzie Investments to implement ESG investing strategies more efficiently and develop sophisticated ESG-focused insights and investment products, with BigQuery playing a central role in powering these analytics workloads moving forward. Don Huff, the Global Head of Client Services and Operations at Bloomberg Data Management Services, stated that as capital markets firms are in the process of migrating their workloads to the Cloud, their customers require efficient access to high-quality data in a preferred environment. He expressed excitement about extending their partnership with Google Cloud, aiming to stay at the forefront of innovation in financial data management and to enhance their customers' enterprise analytics capabilities. Stephen Orban, the VP of Migrations, ISVs, and Marketplace at Google Cloud, stated that Google Cloud and Bloomberg share a common commitment to empowering customers making data-driven decisions to power their businesses. He mentioned that the expanded alliance between the two companies would allow customers to effortlessly integrate Bloomberg's leading datasets with their own data within BigQuery. This would simplify the process of conducting analytics with valuable insights related to financial markets, regulations, ESG, and other critical business information.

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Big Data Management

Sigma and Connect&GO Redefine Data Analytics for Attraction Industry

Sigma Computing | November 07, 2023

Sigma and Connect&GO have recently introduced the new Connect&GO reporting tool, an advanced embedded analytics solution that empowers attractions worldwide to enhance operational efficiency, boost revenue, and evaluate their data in real-time. This no-code platform, a result of Sigma's cloud analytics expertise and Connect&GO's integrated technology, offers an intuitive and customizable dashboard for real-time data insights. It simplifies data analytics, reporting, and sharing, making it suitable for a wide range of attractions industry customers, including marketing, finance, and operations managers, as well as C-suite executives. The new Connect&GO reporting tool equips attractions industry customers with the ability to make informed decisions through customizable dashboards. Operators can effortlessly upload data sets, such as forecasts and projections from various systems, and compare them in real-time with actual data, including budgets. This live data and insights allow them to delve into the granular details of their business, enabling them to address day-to-day challenges, compare data sets, and plan for the future more accurately. These capabilities enable attractions to improve guest satisfaction, foster collaboration, ease the burden on engineering teams, and ultimately generate new revenue streams. For instance, park management can use better data to predict attendance, adjust staffing levels as needed, and ensure appropriate retail, food, and beverage inventory to enhance the guest experience. Sigma has rapidly established itself as a go-to cloud analytics platform, experiencing significant growth over the past years and earning numerous awards, including Snowflake BI Partner of the Year 2023. Sigma's success can be attributed to its mission of removing traditional barriers to data access and empowering business users to extract maximum value from live data without requiring technical expertise. Platform users can directly access and manage data stored in a cloud data warehouse without the involvement of a data team. With a familiar and intuitive interface, they can easily explore data and test different scenarios, gaining new insights and the context needed for decision-making. In contrast to legacy technology platforms that keep data isolated and operations disjointed, Connect&GO's cutting-edge solution, Konnect, is a fully integrated system that enables operators to oversee every aspect of their business seamlessly. This platform uniquely provides operators with real-time data, making it effortless to manage eCommerce, access control, point-of-sale, and cashless payments through proprietary Virtual Wallet technology. With its configurable interface and connected RFID wearables, Konnect enables operators to curate premium guest experiences that drive revenue and enhance engagement. About Sigma Computing Sigma Computing is a prominent cloud analytics solutions provider, offering business users seamless access to their cloud data warehouse for effortless exploration and insight gathering. With its intuitive spreadsheet-like interface, Sigma eliminates the need for coding or specialized training, enabling users to effortlessly navigate vast datasets, augment them with new information, and conduct real-time 'what if' analyses on billions of rows of data. About Connect&GO Connect&GO is a leading integrated technology and RFID solutions provider for the attractions industry. Its flexible operations management platform seamlessly integrates e-commerce, food & beverage, point-of-sale, access control, RFID, and cashless payments using its proprietary Virtual Wallet technology, consolidating all data in one place. The company helps drive revenue and maximize guest engagement with valuable real-time data insights. Connect&GO serves amusement and water parks, family entertainment centers, zoos & aquariums, and other attractions worldwide, integrating user-friendly wearable technology into extraordinary experiences.

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Big Data Management

NetApp Empowers Secure Cloud Sovereignty with StorageGRID

NetApp | November 08, 2023

NetApp introduces StorageGRID for VMware Sovereign Cloud, enhancing data storage and security for sovereign cloud customers. NetApp's Object Storage plugin for VMware Cloud Director enables seamless integration of StorageGRID for secure Object Storage for unstructured data. NetApp's Sovereign Cloud integration ensures data sovereignty, security, and data value while adhering to regulatory standards. NetApp, a prominent global cloud-led, data-centric software company, has recently introduced NetApp StorageGRID for VMware Sovereign Cloud. This NetApp plugin offering for VMware Cloud Director Object Storage Extension empowers sovereign cloud customers to cost-efficiently secure, store, protect, and preserve unstructured data while adhering to global data privacy and residency regulations. Additionally, NetApp has also unveiled the latest release of NetApp ONTAP Tools for VMware vSphere (OTV 10.0), which is designed to streamline and centralize enterprise data management within multi-tenant vSphere environments. The concept of sovereignty has emerged as a vital facet of cloud computing for entities that handle highly sensitive data, including national and state governments, as well as tightly regulated sectors like finance and healthcare. In this context, national governments are increasingly exploring ways to enhance their digital economic capabilities and reduce their reliance on multinational corporations for cloud services. NetApp's newly introduced Object Storage plugin for VMware Cloud Director offers Cloud Service Providers a seamless means to integrate StorageGRID as their primary Object Storage solution to provide secure Object Storage for unstructured data to their customers. This integration provides StorageGRID services into the familiar VMware Cloud Director user interface, thereby minimizing training requirements and accelerating time to revenue for partners. A noteworthy feature of StorageGRID is its universal compatibility and native support for industry-standard APIs, such as the Amazon S3 API, facilitating smooth interoperability across diverse cloud environments. Enhanced functionalities like automated lifecycle management further ensure cost-effective data protection, storage, and high availability for unstructured data within VMware environments. The integration of NetApp's Sovereign Cloud with Cloud Director empowers providers to offer customers: Robust assurance that sensitive data, including metadata, remains under sovereign control, safeguarding against potential access by foreign authorities that may infringe upon data privacy laws. Heightened security and compliance measures that protect applications and data from evolving cybersecurity threats, all while maintaining continuous compliance with infrastructure, trusted local, established frameworks, and local experts. A future-proof infrastructure capable of swiftly reacting to evolving data privacy regulations, security challenges, and geopolitical dynamics. The ability to unlock the value of data through secure data sharing and analysis, fostering innovation without compromising privacy laws and ensuring data integrity to derive accurate insights. VMware Sovereign Cloud providers are dedicated to designing and operating cloud solutions rooted in modern, software-defined architectures that embody the core principles and best practices outlined in the VMware Sovereign Cloud framework. Workloads within VMware Sovereign Cloud environments are often characterized by a diverse range of data sets, including transactional workloads and substantial volumes of unstructured data, all requiring cost-effective and integrated management that is compliant with regulated standards for sovereign and regulated customers. In addition to the aforementioned advancements, NetApp also announced a collaborative effort with VMware aimed at modernizing API integrations between NetApp ONTAP and VMware vSphere. This integration empowers VMware administrators to streamline the management and operations of NetApp ONTAP-based data management platforms within multi-tenant vSphere environments, all while allowing users to leverage a new micro-services-based architecture that offers enhanced scalability and availability. With the latest releases of NetApp ONTAP and ONTAP Tools for vSphere, NetApp has significantly made protection, provisioning, and securing modern VMware environments at scale faster and easier, all while maintaining a centralized point of visibility and control through vSphere. NetApp ONTAP Tools for VMware provides two key benefits to customers: A redefined architecture featuring VMware vSphere APIs for Storage Awareness (VASA) integration, simplifying policy-driven operations and enabling cloud-like scalability. An automation-enabled framework driven by an API-first approach, allowing IT teams to seamlessly integrate with existing tools and construct end-to-end workflows for easy consumption of features and capabilities.

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Big Data Management

Google Cloud and Bloomberg Unite to Accelerate Customers Data Strategies

Bloomberg | November 06, 2023

Bloomberg and Google Cloud integrate Data License Plus (DL+) with BigQuery for efficient data access and analytics. Customers can access fully modeled data within BigQuery, eliminating data preparation time. Mackenzie Investments adopts DL+ ESG Manager to host the acquisition, management, and publishing of Multi-vendor ESG data. Bloomberg has unveiled a new offering designed to accelerate the data strategies of Google Cloud customers by integrating Bloomberg's cloud-based data management solution, Data License Plus (DL+), with Google Cloud's fully managed, serverless data warehouse, BigQuery. Now, with access to Bloomberg's extensive experience modeling, managing, and delivering vast quantities of complex content, mutual customers can receive their Bloomberg Data License (DL) data, entirely modeled and seamlessly combined within BigQuery. As a result, organizations can leverage the advanced analytics capabilities of Google Cloud to extract more value from critical business information quickly and efficiently with minimal data wrangling. Through this extended collaboration, customers can harness the powerful analytics features of BigQuery and tap into Bloomberg's extensive collection of datasets available through Data License to power their most essential workloads. Bloomberg's Data License content offers a wide variety, including reference, pricing, ESG, regulatory, estimates, fundamentals, and historical data, supporting operational, quantitative, and investment research workflows, covering over 70 million securities and 40,000 data fields. Key benefits include: Direct Access to Bloomberg Data in BigQuery: Bloomberg customers can seamlessly access Bloomberg Data License content within BigQuery, allowing for scalable use across their organization. This eliminates the time-consuming tasks of ingesting and structuring third-party datasets, thereby accelerating the time-to-value for analytics projects. Elimination of Data Barriers: Google Cloud and Bloomberg will make Bloomberg's DL+ solution available to mutual customers via BigQuery. This allows for the delivery of fully modeled Bloomberg data and multi-vendor ESG content within their analytics workloads. In a recent announcement, Bloomberg revealed that Mackenzie Investments has selected DL+ ESG Manager to host the acquisition, management, and publishing of multi-vendor ESG data. This move positions Mackenzie Investments to implement ESG investing strategies more efficiently and develop sophisticated ESG-focused insights and investment products, with BigQuery playing a central role in powering these analytics workloads moving forward. Don Huff, the Global Head of Client Services and Operations at Bloomberg Data Management Services, stated that as capital markets firms are in the process of migrating their workloads to the Cloud, their customers require efficient access to high-quality data in a preferred environment. He expressed excitement about extending their partnership with Google Cloud, aiming to stay at the forefront of innovation in financial data management and to enhance their customers' enterprise analytics capabilities. Stephen Orban, the VP of Migrations, ISVs, and Marketplace at Google Cloud, stated that Google Cloud and Bloomberg share a common commitment to empowering customers making data-driven decisions to power their businesses. He mentioned that the expanded alliance between the two companies would allow customers to effortlessly integrate Bloomberg's leading datasets with their own data within BigQuery. This would simplify the process of conducting analytics with valuable insights related to financial markets, regulations, ESG, and other critical business information.

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Big Data Management

Sigma and Connect&GO Redefine Data Analytics for Attraction Industry

Sigma Computing | November 07, 2023

Sigma and Connect&GO have recently introduced the new Connect&GO reporting tool, an advanced embedded analytics solution that empowers attractions worldwide to enhance operational efficiency, boost revenue, and evaluate their data in real-time. This no-code platform, a result of Sigma's cloud analytics expertise and Connect&GO's integrated technology, offers an intuitive and customizable dashboard for real-time data insights. It simplifies data analytics, reporting, and sharing, making it suitable for a wide range of attractions industry customers, including marketing, finance, and operations managers, as well as C-suite executives. The new Connect&GO reporting tool equips attractions industry customers with the ability to make informed decisions through customizable dashboards. Operators can effortlessly upload data sets, such as forecasts and projections from various systems, and compare them in real-time with actual data, including budgets. This live data and insights allow them to delve into the granular details of their business, enabling them to address day-to-day challenges, compare data sets, and plan for the future more accurately. These capabilities enable attractions to improve guest satisfaction, foster collaboration, ease the burden on engineering teams, and ultimately generate new revenue streams. For instance, park management can use better data to predict attendance, adjust staffing levels as needed, and ensure appropriate retail, food, and beverage inventory to enhance the guest experience. Sigma has rapidly established itself as a go-to cloud analytics platform, experiencing significant growth over the past years and earning numerous awards, including Snowflake BI Partner of the Year 2023. Sigma's success can be attributed to its mission of removing traditional barriers to data access and empowering business users to extract maximum value from live data without requiring technical expertise. Platform users can directly access and manage data stored in a cloud data warehouse without the involvement of a data team. With a familiar and intuitive interface, they can easily explore data and test different scenarios, gaining new insights and the context needed for decision-making. In contrast to legacy technology platforms that keep data isolated and operations disjointed, Connect&GO's cutting-edge solution, Konnect, is a fully integrated system that enables operators to oversee every aspect of their business seamlessly. This platform uniquely provides operators with real-time data, making it effortless to manage eCommerce, access control, point-of-sale, and cashless payments through proprietary Virtual Wallet technology. With its configurable interface and connected RFID wearables, Konnect enables operators to curate premium guest experiences that drive revenue and enhance engagement. About Sigma Computing Sigma Computing is a prominent cloud analytics solutions provider, offering business users seamless access to their cloud data warehouse for effortless exploration and insight gathering. With its intuitive spreadsheet-like interface, Sigma eliminates the need for coding or specialized training, enabling users to effortlessly navigate vast datasets, augment them with new information, and conduct real-time 'what if' analyses on billions of rows of data. About Connect&GO Connect&GO is a leading integrated technology and RFID solutions provider for the attractions industry. Its flexible operations management platform seamlessly integrates e-commerce, food & beverage, point-of-sale, access control, RFID, and cashless payments using its proprietary Virtual Wallet technology, consolidating all data in one place. The company helps drive revenue and maximize guest engagement with valuable real-time data insights. Connect&GO serves amusement and water parks, family entertainment centers, zoos & aquariums, and other attractions worldwide, integrating user-friendly wearable technology into extraordinary experiences.

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