Today, data is invaluable to every business irrespective of its nature and size. As the information is growing consistently, the role of data analytics has become an essential element in business growth. To compete with the opposition, you have to remain updated with the changes in business analytics. You may have heard about “Smart Data Discovery,” it is leading as a supreme differentiator across the organizations. Organizations can get clear insights by concentrating on building models and coordinating information for improving it and automating the tasks. Therefore, the demand for skilled data analysts has increased in the market.

For data analytics, augmented analytics is the best option which can iteratively play out the data-to-insight-to-action like setting up the data, decoding data patterns and building models, and conveying and operationalizing the information discoveries. It saves both time and assets utilized for getting relevant business insights from the information.

With the help of Machine Learning and Natural Language Generation (NLG), augmented analytics makes data-insights automated. These data-insights can help with faster and proper decision making. Hence, augmented analytics is a new trend in the field of business intelligence (BI), data analytics and enabling analytics-driven organization. Thus, it has become the best choice for the organizations as the platform capacities are developing.

For those who are interested in choosing their business solutions, or managing an analytical solution implementation, they should understand the features and functions of augmented analytics.

Augmented Analytics Function

Over the past several years, with the help of AI, NLP, and many other technologies, different advanced techniques have been developed in the automated analytics field. However, apart from the present capacities of data analytics tools for visualizing and grouping data, the future of augmented analytics, seems more exceptional. It gives historical reports and dashboards, as well as offers automated and actionable prescient and prescriptive direction.

By using augmented analytics, complicated and time-consuming evaluations will be solved faster and more comfortable. It analyzes the data automatically, translates the shrouded designs into data and builds models using them. To illustrate the data and to give a proposal for making an appropriate move, Artificial Intelligence (AI) programmes are used. Organisations can examine their speculation and hypotheses as they can decipher their information and access key data using different statistical algorithms. Augmented analytics accomplishes things like exploring new data-sets, identification of leads, analyzing the result, agitation of customer and more.

                                                                                                            [Source: Gartner]

Here are some reasons that you should think about augmented analytics & data preparation for your future business

• Traditional data discovery methods are expensive, time-consuming, and slow in providing desired results.
• For predicted results, business owners need to depend on data analyst and data scientist who are trained.
• As this procedure is tedious, more than frequently, decisions could be made based on “gut feeling” instead of on logical expectations given statistical analysis.
• Entrepreneurs don't have the skill and time to analyze the content, yet in the meantime, they require precise, impartial information to make solid business decisions. Augmented analytics facilitates these.

Here are the facilitates of  advanced analytics and augmented data preparation: 

• Data scientists & IT groups will be able to concentrate on tactical things and special projects.
• These advanced technologies in smart data discovery, other modern strategies and plannings can emphatically affect ROI and TCO.
• Accessible augmented analytics makes Citizen Data Scientists and enhances responsibility and empowerment.
• This analytics will help organizations to make the right decisions,  more precise business predictions and quantifiable analysis of product and pricing, financials, production and different parts of the business.
• Augmented data preparation and related devices will enhance the data range, user adoption, social BI integration, and information literacy.

Though It is not simple to remain alongside the terms, strategies, and solutions in the analytics space, it is well worth the effort. This market is changing rapidly with new tools and advancement introduced each year.

Regardless of whether you are an IT expert, an in-house IT proficient, a middle manager or a senior official, it is essential to observe the progress of business analytics and the related technology. Each business needs to see how these solutions can and will influence clients, procedures and work process.

Providing your team with the advanced tools like Sisense, Domo, Tableau, QlikView...etc & training, and an easy method to deal with the vast amount of data is essential to your business achievement and will make each employee an advantage for your organization.

Factors for the Organizations to Consider Augmented Analytics

Provision of  Agile centralized business intelligence

Cloud-based deployments, concerning the advanced analytics and business insights platforms. Next-generation augmented analytics has empowered data analytics delivery at a significantly faster pace over the organization while at the same time utilizing far fewer assets.

Mutually beneficial business interactions 

Enterprises are expected to provide access to the curated data to clients by giving double business value to those who invest in augmented analytics by the year 2020. The data can be shared over the organizations through the cloud, along these lines advancing their analytics and those of others for obvious advantages through consistent, networked integration of data and analytics over their enterprises.

Decentralized analytics

Expansion of the corporate information model has not been made possible with the decentralized groups and individual clients without compromising data governance. Standard definitions and key measurements form bound together semantic layer that keeps up consistency irrespective of the client's area.

A comprehensible user interface 

Simple to use tools that help an extensive variety of analytics work process capacities form the basis of augmented analytics in business. Advanced augmented analytics give a consumer-grade UI that is more instinctive, rich, and user-friendly for the business people and gives them more power.

Governed data discovery 

It is possible to help the work process from data to self-service analytics, a  record system, and IT-managed content. It would then be able to be governed, reused, and advanced as ensured data and analytics content.

Summary 

Augmented analytics has changed efficiently the whole work process of analytics and the manner by which data analysts get information and work on insights. It is an approach that automates insights. It will lead to reach beyond data scientists and transform the organizations exceptionally.