There are three types of data analytics: descriptive, predictive, and prescriptive. Descriptive analysis (descriptive statistics), as the name suggests, “describes” or summarizes raw data and makes it interpretable to humans. Descriptive analytics describes the past. It uses data aggression and data mining techniques to get an insight into the past and tries to answer the question, “What has happened?” These insights help the business make better plans and succeed in the future. Descriptive statistics summarizes the sample and the observations that have been made. Such summaries can be either quantitative or visual. Quantitative summaries are in the form of summary statistics and visual summaries are in the form of graphs to provide more simplicity. These summaries may either form part of a more extensive statistical analysis, which is the basis of the initial description of the data, or they may be sufficient in and of themselves for a particular investigation. Many types of data can be summarized with the help of descriptive analytics. For example, investors and brokers perform analytical and empirical analysis on their investments, which helps them in making better investment decisions in the future. Descriptive analysis can also be called post-mortem analysis. It is used for almost all management reporting, such as marketing, sales, finance, and operations. To have competitive edge, companies use advanced analytics, which also supports them in forecasting future trends. The forecasting allows companies to make optimized decisions, thus increasing their profitability.
Over the years, the increasing adoption of big data has been leading to rising volumes of data generated and advancements in digital technology, which is driving the descriptive analytics market. Moreover, other major factors driving the growth of descriptive analytics market are the rising need for analytics and the increasing return on investments (ROI). However, huge investment costs are restraining the growth of the descriptive analytics market. Also, the lack of data connectivity and integration are factors expected to hinder the growth of the market. Enterprises are adopting analytics techniques to analyze structured and unstructured data, which enables them to make better decisions, leading to the creation of more opportunities for the descriptive analytics market in the coming years. Also the growth of e-commerce is also an opportunity for the e-commerce market.
The global descriptive analytics market is segmented on the basis of verticals and regions. In terms of verticals, the market can be segmented into banking, financial services, and insurance (BFSI), telecom, retail & consumer goods, health care, and energy & utilities. The market segments on the basis of geographical regions are North America, Europe, Latin America, Asia Pacific, and Middle-East and Africa (MEA). North America is expected to lead the descriptive analytics market, followed by Western Europe, due to the growing spending on the Internet of Things (IoT) and advanced technologies in these regions.
Industry participants leading the descriptive analytics market with the most significant developments are IBM Corporation, Oracle Corporation, Dell Inc., Accenture Plc., TCS Ltd., Infosys Ltd., SAP SE, KNIME.COM AG, Pegasystems Inc., and Microsoft Corporation, among others.
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