Transparency Market Research
Dark Analytics Market - Overview
Raw information generated in ever-expanding volumes by social media, transactional systems, search engines, and countless other technologies, remain unstructured and unanalyzed. This data can be used to reform decision making and validate or clarify assumptions. Organizations today have explored a way to analyze nontraditional data sources, such as, audio, image, video files, and the recent torrent of sensor and machine information generated by the Internet of Things. However, advancement in cognitive analytics is making it possible for companies to analyze these unexploited data and derive insights that can be utilized for decision making process across the business. Dark analytics primarily focuses on raw text-based data or unstructured data/dark data that has not been analyzed. Dark data generally refers to raw data or information hidden in tables, text, figures, etc.
The dark analytics market deals with the exploitation of dark data which is difficult to access. However, advanced data discovery tools and gathering techniques have opened up ways to find several new insights. Once these unstructured databases are collected, companies are increasingly leaning on cutting-edge analysis tools, such as, big data analytics and open source machine learning, to make strides in organizational learning. Organizations are realizing the massive risks associated with losing competitive edge in regulatory issues that comes with not processing and analyzing this data. Using analytics tools, users can develop end-to-end data pipelines to handle extraction, integration, and prediction of data by machine learning techniques.
Dark Analytics Market – Drivers & Restraints
Immediate analysis of real-time information for mining insights for decision making is the major factor responsible for driving the growth of dark analytics market. The market is also driven by other factors, such as, efficiency in terms of money, resources, and time in processing unstructured data, aid to minimize the accumulation or growth of unstructured/dark data by converting it into valuable real-time information, and making an efficient use of every data point. However, risks and security concerns associated with data and data storage costs are expected to hinder the growth of dark analytics market during the forecast period.
The global dark analytics market can be segmented based on analytics type, dark data type, enterprise size, and vertical. In terms of analytics type, the market can be bifurcated into four major categories: prescriptive, predictive, diagnostic, and descriptive. Based on dark data type, the market can be fragmented into customer, business, and operational dark data. By enterprise size, the market can be categorized into SMEs and large enterprises. In terms of vertical, the global dark analytics market can be segregated into BFSI, telecom & IT, media & entertainment, transportation, retail & e-commerce, utilities, health care, government, and education.
Dark Analytics Market - Segmentation
The global dark analytics market can also be classified in terms of region into North America, South America, Europe, Asia Pacific, and Middle East & Africa. North America is anticipated to account for a major share of the market during the forecast period. This can be ascribed to the large number of dark analytics startups providing services to various industries in the region. Moreover, cloud service providers and leading analytics companies are based in the region. Increase in the adoption of IoT, emergence of the machine learning and AI technology, and rise in the number of business applications are the key factors projected to drive the growth of the dark analytics market in North America. Asia Pacific is expected to be a rapidly growing market of dark analytics owing to the rise in adoption of analytics in enterprises in the region.
Dark Analytics Market – Key
Major players active in the development of dark analytics include Microsoft Corporation, IBM Corporation, Deloitte, EMC Corporation, SAP SE, Teradata, Hewlett-Packard, VMware, Inc., Apple Inc., Amazon Inc., SynerScope, Komprise, Quantta Analytics, and Zoomdata.
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