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Top 10 Analytics Technologies by Technology (Analytics-As-A-Service, Streaming Analytics, Edge Analytics, Data Lakes, Social Media Analytics, Predictive Analytics, Security Analytics, High-Performance Data Analytics, Content Analytics, and Video Analytics)
“Growing volume and variety of business data across industry verticals is expected to drive the growth of the analytics technologies market during the forecast period”
The top 10 analytics technologies market is expected to grow at a significant rate during the forecast period. This report covers the major analytics technologies such as analytics as a Service, streaming analytics, edge analytics, Data Lakes, social media analytics, predictive analytics, security analytics, high-performance data analytics, content analytics, and video analytics, along with their market trends between 2015 and 2020/2016 and 2021.
“Emergence of Internet of Things (IoT) enabled and connected technologies fueling the growth of the real-time streaming analytics market”
Internet connectivity and devices offer organizations with tremendous opportunity to extract relevant data, such as consumer behavior in retail outlets, real-time marketing analysis, sensor-driven decision analytics, and instantaneous control response in complex autonomous systems. IoT connects companies and governments with all smart prospects, such as smart cities, smart transportation, smart healthcare, and smart energy. This helps them to get all the data about the market condition. IoT is generating vast amounts of data in different varieties from millions of sources in real time at a high velocity on a daily basis. Thus, IoT provides numerous opportunities in real-time remote management, monitoring, and insight generation from smart connected devices, such as mobile phones or connected cars, which is driving the streaming analytics market.
“Potential for in-depth insights to drive competitive advantage expected to boost the growth of the data lakes market during the forecast period”
As global competition continues to shrink profit margins, companies are seeking newer ways to increase revenue and reduce expenses. It is necessary for businesses to combine demographics and competitive information with customer data to evaluate the business performance relative to their competitors. As organizations are running multi-channel marketing campaigns these days, they end up having large quantities of flowing and unstructured data from various sources. It is very important for organizations of all sizes to focus on analyzing sales and market saturation in specific territories and identifying gaps to stay ahead in the competition. Additionally, customers demand for better quality, lower price, and faster delivery of their products and services. Hence, organizations across industries are under pressure to achieve efficiency and effectiveness with limited resources. In a competitive environment across industry verticals where every bit of data matters, the Data Lakes can be very useful to organizations. Thus, companies can leverage Data Lake solutions and services to gain a competitive edge.
“Higher and cheaper computing power driving the growth of the predictive analytics market”
Processing speed and memory have been increasing at an exponential rate day by day. Earlier, it might have taken hours or days to run a predictive model, which now takes a few minutes or seconds. The traditional systems were not able to handle large amounts of data sets with multiple attributes. Traditional machine learning uses statistical analysis, based on the total data set and it is often very difficult to afford the computing power needed to interpret big data that could be structured or unstructured. With the computing power increasing and the price per Central Processing Unit (CPU) dropping, predictive analytics is now much more practical for organizations to use. Organizations have the ability to analyze very large numbers of records and very large numbers of attributes per record, thereby increasing the predictability.
The major players in the market for top 10 analytics technologies include IBM Corporation (U.S.), Oracle Corporation (U.S.), SAS Institute (U.S.), SAP SE (Germany), Microsoft Corporation (U.S.), Dell Technologies, Inc. (U.S.), Cisco Systems (U.S.), Hewlett-Packard Enterprise (U.S.), GoodData Corporation (U.S.), and Informatica Corporation (U.S.).
This research report categorizes the top 10 analytics technologies market on the basis of type, software, service, application, business function, data type, vertical, and region. The report also discusses the major drivers and restraints pertaining to all the 10 markets, along with the industry trend analysis.
Reasons to Buy the Report:
The report would help the leaders/new entrants in this market in the following ways:
1. This report segments the top 10 analytics technologies market comprehensively and provides the closest market size estimation for all subsegments across different regions.
2. The report would help stakeholders understand the pulse of the market and provide them with the information on key drivers and restraints for market growth.
3. This report would help stakeholders understand their competitors better and gain more insights to improve their position in the business. The report also includes competitor ecosystem, new product launches & developments, partnerships, and mergers & acquisitions.