The amount of data generated now-a-days is endless, data analysis has become an imperative component of business advancement. To be on the side of competitive advantage, businesses requires to remain updated with the up gradation of business analytics. In 2017, the expression “smart data discovery” emerged and at present it is dominant as differentiator crosswise over various businesses. To get a clear overview and understanding over the topic, most organizations are currently focusing on creation of models and bring together comprehensive information for streamlining it and tasks automation. This has opened gates of immense opportunity for the skilled data scientists, widely in the market.
to the propelling benefits of augmented analytics, industry verticals are highly adopting the technology. BFSI accounted largest market share in 2017, predicted to be near one-fourth share of the total revenue. This segment is expected to be dominant up to 2025, owing to increasing demand for augmented analytics in the sector to leverage the power of AI to increase revenue, reduce costs and comply with regulations. However, healthcare and life sciences will grow faster due to surge in demand for generating insights for healthcare scientist & researchers, hospital managers, optimized care services and pharmaceutical experts to boost drug discovery, analyze patient turnover data and reduce time to market lifesaving drugs.
Furthermore, studies anticipate that in the coming next two years, 40% of the tasks that are currently based on data science will get automated. This will surge the application of augmented analytics in software segment. Among all other applications, software segment will dominate and grow fastest by the 2025. This hold highest share in 2017, accounting 3/5th of the share out of total revenue and continue its dominance in the forthcoming years. Service segment is anticipate to grow at the fastest CAGR of 32% through 2025 owing to aggrandized demand for planning, maintenance, training and support services and personnel associated with augmented analytics.
The on premise deployment segment accounted the largest share in 2017, holding a value of three-fifths of the total market revenue. However, the cloud segment is anticipated to grow at the fastest pace during the forecast period. Due to higher preference coming from small and medium organizations due to the direct IT control, low capital cost & maintenance, faster data processing, improved internal data delivery & handling and efficient resource utilization.
of these data scientists opt for Augmented Analytics as it repetitively develop the data into more useful information like interpreting data, assembling data and building models, and operationalizing and disseminating the data findings. It is a time and assets saver strategy for getting key business insights from the available data.
Analytics uses natural language processing and machine learning to automate data analysis and representing the insights. This has facilitated non-technical users to automate key aspects of their data analytics by amalgamating artificial intelligence (AI) with business intelligence (BI). These platforms have benefited end-users on two fronts. First, data scientists and technical analysts are freed from basic reports and running routine. This has empowered them handle complex data science projects and queries. Second, similar to interacting with Siri and google, non-technical users have augmented analytics solutions by asking questions and getting answers instantly. Thereby, drastic reduction in reporting time and accelerating performance and strategy.
The technology has major benefits for marketers and non-technical users as all their daily operations are transformed with help of augmented analytics. Brand managers, chief marketing officers and other employees rely on an analytics team for data analysis and reporting. Beginning with one-off questions to profound research and planning, all these users depend on third parties and outsourcing which is costly and inefficient. Augmented solutions have transferred the power back to the marketing users. As explained in "CPG Analytics: The Definitive Guide," "From opportunity analysis to churn analytics to attribution studies and even customer journey mapping, new advancements in business intelligence make it so that you can make quick and effective decisions."
Business enterprises have adopted AA to drive technological disruption. Chevron Corp. is an early adopter of Google’s AutoML technology. The technology was designed to aid users who lack of machine learning expertise to create and analytical models. Chevron’s seismic imaging and processing team implemented alpha version of AutoML Vision image analysis tool to see through internal documents to evolve new opportunities for oil drilling. To segregate documents that have spatial information related to prospective oil locations in the Gulf of Mexico, the Chevron team started a search on geologic map to emphasize documents that contains embedded map images. The next step is to run an analytic model built on AutoML Vision which was created in a way that identify 60 plus geologic labels on the map images.
On the geographical front, North America owns more than one-third of the total market is expected to maintain its growth rate during the forecast period due to the region being early adopters of augmented analytics solutions. However, Asia-Pacific would compete with North America with equal potential and fastest CAGR owing to the demand for generating valuable insights among enterprises, increasing adoption of AI driven technologies, growing automation in India and emerging augmented workplaces in India, China and Japan.
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