Increasing Machine Learning Leading to Increase in Data Generation

The rising need for data driven decision making and understanding undiscovered trends and pattern has made data discovery as a hot topic on both business and IT sides of organization. Data discovery can contribute significantly towards interpretation and sharing of insights from data analytics, enabling non-technical SMBs to perform data discovery in a self-directed manner. Implementation of chart diagrams and maps, the growth in the number and variety of visualizations available in graphics libraries are supporting advanced visual analysis, allowing companies to go beyond simple bar and pie charts to express more advanced insights about quantitative information. Data discovery platform is a user-driven process and a part of business intelligence architecture mainly aimed at creating interactive reports and exploring data from various back-end systems and sources for searching for patterns or specific items from the data set. Data discovery software and services are gaining traction attributed to increased need of the voluminous data getting generated in organizations on a daily basis.

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Data discovery can be defined as a decision-making platform to assimilate, structure and refine data obtained from stored and streaming data sources. A data discovery platform provides tools for traditional On Line Analytical Processing (OLAP) capabilities and easy-to-use data science capabilities for less experienced users. Data discovery products also provide a wide array of analysis techniques, which include statistical analysis, text analysis, and graph analysis, which can be considered as the major factors for the growth of the data discovery market.

Banking, Financial Services, and Insurance

Data discovery tools help to tackle issues such as insufficient data modeling capabilities of bank employees and allows bank personnel to interpret the data to enhance customer experience. It helps to identify potential customer segments and trap them with effective offers. More significantly, data discovery is beneficial to banks and financial service providers to build business models and take proper investment decisions with substantial risk analysis.

Retail and Ecommerce

Growing penetration of online shopping among consumers have fueled the growth of the e-commerce sector across the world. Such e-commerce players have tremendous customer data collected over the years with constant addition of petabytes of data every day. The data collected through social media in the form of comments, posts, and blogs prove helpful to make demand forecasting, customer segmentation, and profitability analysis.

Telecommunications and IT

Data discovery tools help the telecom companies to view customer experience and satisfaction independently across each channel. This facilitates them to calculate prices and build marketing plans of new services, improve average revenue per user, enhance customer loyalty, and minimize loss. Customer retention and acquisition with data analysis is one the major focus areas for telecom companies, as they can develop effective marketing campaigns and product offerings.

Manufacturing

Manufacturing companies seriously focus on analyzing the data collected from numerous sources, including historical production data to sensor signals, to identify production, labor, product quality issues and address them in the minimal time efficiently. The manufacturing industry is recognizing the benefits of data discovery tools and has started implementing the solution in various processes.

Major vendors that offer data discovery offerings globally are Tableau Software (U.S.), Datawatch Corporation (U.S.), TIBCO Software (U.S.), SAP SE (Germany), Datameer, Inc. (U.S.), Qlik Technologies (U.S.), and ClearStory Data (U.S.), These vendors adopted different types of organic as well as inorganic growth strategies such as new product launches, partnerships & collaborations, and mergers & acquisitions to expand their offerings in the data discovery market.

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