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Augmented Analytics: The Future of Data and Analytics

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Augmented Analytics: The Future of Data and Analytics

A brief discussion on the topic of augmented analytics and what this data tool can do for data teams and businesses alike.

· Big Data Zone ·
Free Resource

With the rising need and importance for data, many next generation technologies and data processing tools are coming into the spotlight. Today, becoming data-driven is a key priority for many advanced organizations. In order to sustain a good position in the industry, organizations need to adopt an advanced data processing tool such as augmented analytics.

Augmented analytics uses Artificial Intelligence (AI) and machine learning to augment human efforts to evaluate data. It beats the traditional analysis tools by automating data insights and providing clearer information. According to Forbes, 89% of industry leaders believe that Big Data will transform business operations in the same way the Internet did. Also, enterprises that don’t implement a business intelligence (BI) strategy to gather, evaluate, and apply that information in a meaningful way will be left in the dust. Here’s where an advanced data analytical tool like augmented analytics comes into the picture. According to a report by Allied Analytics, due to the growing adoption of next-generation technologies, such as augmented analytics, the global augmented analytics market size is expected to reach $29 million by 2025.

Some of the reasons driving the growth of the global augmented analytics market are raising awareness of businesses to consume evolving streams of data from numerous sources, growing need to increase efficiency and democratize the analytics, and surge in need to make the work stress-free for citizen data scientists and business managers. Currently, the implementation of augmented analytics is a major factor in banking, financial services, and insurance industries.

Role of Augmented Analytics in Converting Big Data to Smart Data

For obtaining improved data insights, augmented analytics will recast big Data into smart data. Being an advanced data processing tool, augmented analytics is able to derive the real essence of insights from big data. Many businesses are already focused on evolving smart data analytics solutions to obtain valuable insights from their big data sets.

Smart data will assist many businesses in reducing the threat of losing data. It will also improve a series of activities such as product development, operations, consumer experience, predictive maintenance, and innovation.

Impact of Augmented Analytics Tools on Enterprises

The business intelligence (BI) market has seen enormous development in recent years. The largest area where augmented analytics will be of use is business analytics. The BI industry is being disturbed because augmented analytics threatens to lower the barrier of entry for the industry. Augmented analytics technology can help data scientists to automate the process of organizing data, analyzing data, and constructing models. These systems allow business individuals to obtain data insights directly by asking queries using natural language. With this technology, the need to ask specialists to prepare custom reports that are time-consuming is diminished.

Augmented analytics tools provide organizations with faster data insights, merging machine learning and natural language processing together to automate the process of generating business analytics. According to a forecast by Gartner, augmented analytics will dominate analytics and data science.

Augmented Analytics Has Transformed How Users Approach Data

Today, augmented analytics is a highly popular data analytics tool in the market, which does not require any involvement of expert data scientists. With this tool, the wall between the people asking questions and getting to the answers has collapsed. Various facets of business stand to profit from a shift to augmented analytics. Some of the benefits of adopting to augment analytic are as follows:

Benefits for Data Scientists

Data scientists and technical analysts will no longer have to run routine and basic reports. Augmented analytics will allow them to charge ahead and solve more complex queries and data science projects with advanced AI and machine learning. In turn, this advanced work will benefit the business by giving it a leg up on the competition.

Benefits for Marketers:

Augmented analytics will change the way marketing and other non-technical individuals perform their daily operations. Marketing executives, brand managers, and other employees who fall under the marketing umbrella often depend on an analytics team for in-depth research, planning, and reporting. This dependency of marketing professionals on third-parties makes their work time consuming, inefficient, and expensive. With the development of very efficient augmented analytics tools, the control is back in the hands of the marketing professionals.

Conclusion

From data scientists to marketing professionals, several aspects of business stand to benefit from a switch to augmented analytics. The benefits of augmented analytics are abundant and diverse, and as distinct as the business itself. One of the major benefits of augmented analytics is the availability and access to refined analytical procedures, algorithms, and methods for the average professional user, without training or knowledge of data science or analysis.

The quicker your business gets adapted to this technology, the faster your team will be able to find and exploit growth opportunities.

Topics:
augmented analytics ,big data ,data science ,data analytics

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