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.
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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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