Transforming the future of analytics with self-service and Augmented Analytics

Augmented Analytics is the Future of Data and Analytics

The amount of data that’s available these days has changed the way enterprises functions in their day to day activities. The power of analytics is reshaping a new future for companies worldwide with self-service, and Augmented Analytics being two of its newly launched weapons. In this blog, we would see how future is being transformed using self-service and augmented analytics, and how Taliun plays a key role in it.

How self-service Analytics is contributing?

Self-Service Analytics empowers users to analyze their data by developing rapid reports where users could dynamically modify, drill, or perform several calculations. It solves the problem of resource constraints in any organization. The entire control of their own analytics is given to the business users who could extract maximum value from their application, and their data as well as extend the organization’s business intelligence agility.

To empower users with the power of the self-service analytics, data is at the core of everything, and has gained a lot of popularity in the last decade. It is time-consuming for enterprises to gather actionable insights via the traditional means as seen previously where only the executive level decisions were done with the use of Business Intelligence.

However, as requirements changed, more automated and faster ways to analyze data was the need of the hour. Thus dashboards, reports became a trend, and BI became easier to use which made more users use it. This demand of analytics, and reports resulted in the emergence of self-service capabilities which plays a major role in the IT industries, which otherwise would have suffered from the continuous rise of requirements, and the lack of resources.

Below are some of the key points related to self-service analytics

For daily usage in their workflow, users could create their own reports, dashboards and so on with the help of self-service analytics. Data access, or discovery is faster with the help of certain interactive features which makes life of any enterprise easier. Data resources could be managed better with the help of embedded self-service analytics, and insights could be provided in the application.

How Augmented Analytics is contributing?

The increase in data complexity has increased the problems across the enterprise in taking the best data-related decisions. Despite the greater access to various tools across the analytics stack, there are still some task such as building models, interpreting results, etc., require manual intervention. Validation each, and every pattern of their insights is not possible for users. Hence, augmented reality has gained traction in recent times.

Augmented Analytics or reality is nothing but the augmentation of human intelligence, and contextual awareness with the use of Machine Learning, or Artificial Intelligence techniques. The data preparation, model building, etc., are automated by Augmented analytics with the help of ML.

There is a serious shortage of expert Data Scientist in the modern generation. Augmented analytics addresses such challenges by automating bias prone, and time consuming tasks. It also allows application developers, or Business Analysts create models assisted by Augmented Analytics, and generate insights as well.

A report by Gartner suggested that by 2020, Augmented analytics would dominate the world of Business Intelligence, Machine Learning, Data Science, and so on. As a key data preparing, data management feature, Augmented Analytics would be adopted as mainstream. Conversational chatbots, enterprise applications would also have automated insights embedded within them.

The reduction in time, and elimination of irrelevant insights could be done with Augmented Analytics which would optimize actions, and reduce the risk of missing relevant information. Users would act upon on the most significant insights. Hence, to start using Augmented analytics, enterprises should start to compliment the data, and pilot it for important business problems which requires manual intervention.

How Taliun is contributing in solving your analytical problems

Taliun has been working very closely with different analytics teams from ISVs and enterprises to solve the digital analytics challenge with a solution that is based on no code and self-service approach.

The solution approach focuses on sourcing structured or unstructured data from different sources, aggregating it and then building the actionable reports that can be embedded in any application or device. The platform is currently native to AWS and can be deployed on customers AWS accounts, where any business users can easily leverage the historical data to build charts, metrics, dashboards, reports, visualization or Advance AI. Also since they’re built as web apps, sharing and embedding them is easy to integrate and distribute.

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