Global Dark Analytics Market

Dark analytics is a term used to describe the analysis of data that is not easily searchable or accessible by traditional business intelligence (BI) tools. This data is typically unstructured, unorganized, and difficult to quantify, and is often found in formats such as text, images, and videos. However, with the rise of big data analytics and artificial intelligence, dark analytics is becoming an increasingly important area of focus for businesses across different industries.

The Dark Analytics Market Share is expected to grow USD 3.45 Billion by 2030, at a compound annual growth rate (CAGR) of 26.40% during 2022-2030

One of the main challenges of dark analytics is the sheer volume of data that needs to be analyzed. It is estimated that over 80% of data in organizations is unstructured, and this data is usually not analyzed due to the complexity involved in handling it. However, dark analytics can help to uncover hidden insights from this data that can be leveraged to improve business operations and gain a competitive edge.

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Another challenge with dark analytics is the need for specialized tools and skills to analyze it effectively. Traditional BI tools are not designed to handle unstructured data and require a lot of manual processing and transformation. Companies need to invest in new tools and technologies like natural language processing (NLP), image and video analysis, and machine learning (ML) to better analyze dark data.

One use case of dark analytics is in the healthcare industry. Medical records, X-rays, and other forms of patient data are often unstructured, making it challenging to extract meaningful insights. With the help of specialized tools and technologies, doctors can analyze this data to better diagnose and treat patients. For example, NLP can help to extract relevant medical information from unstructured data like doctor's notes, reports, and correspondence.

In the financial industry, dark analytics can be used to detect fraudulent activities. Traditional methods of detecting fraud rely on structured data such as transaction amounts, dates, and times. However, criminals are becoming increasingly sophisticated, and the challenge of detecting fraud is becoming more difficult. With dark analytics, companies can leverage machine learning algorithms to uncover fraudulent patterns in unstructured data like email communications, chats, and social media interactions.

In conclusion, dark analytics is an emerging area of focus for businesses across different industries. The ability to extract insights from unstructured data requires specialized skills and tools, but the potential benefits are enormous. Businesses that invest in dark analytics will be better positioned to make data-driven decisions and gain a competitive advantage in their respective markets.

Segment Analysis

By component, the market has been segmented into solutions and services. The solution segment is expected to dominate as well as grow with the fastest CAGR.

Based on the deployment, the market has been segmented into on-cloud and on-premise. The on-premise segment is expected to dominate the market.

By application, the market has been segmented into operations, finance, human resources, and marketing. The marketing segment is expected to lead the market.

By industry vertical, the market has been segmented into IT and telecommunication, BFSI, retail and e-commerce, government, healthcare, media and entertainment, and others. The retail and e-commerce segment is expected to lead the market during the forecast period.

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Key Players

The prominent players in the market of dark analytics are IBM Corporation (US), SAP SE (Germany), Symantec Corporation (US), Microsoft Corporation (US), Dell Inc. (US), SAS Institute Inc. (US), Datameer, Inc. (US), Micro Focus (UK), Amazon Web Services, Inc. (US), and Teradata (US).

Others players include Synerscope (The Netherlands), TIBCO Software Inc. (US), Deloitte (US), Veritas (US), Zoho Corporation (US), Commvault (US), Datumize (Spain), AvePoint, Inc. (US) and Zoomdata (US).

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