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Augmented Analytics: Future of Data Inetrpretation and Intelligence

Augmented Analytics: The Future of Data Interpretation and Intelligence

Augmented analytics is here to stay with data interpretation gradually becoming a force to reckon with

The great American management theorist and consultant, Geoffrey Moore once said, "Without big data, you are blind and deaf and in the middle of a freeway."

Data is the newest and perhaps the most sensitive building blocks that the realm of business has ever come across. However, it is also one that requires perceptive treatment – or else its very existence is quite pointless. Simply having data does not suffice. To make sense of it, and make it of use to businesses, the data must lead to some information of worth.

The Process of Data Interpretation

The foundation of any business activity in today's world is based on accurate data insights. To reach adequate information and take necessary business actions, the data is first collected from a number of diverse sources such as web analytics, social media trends, and market surveys.

The collected data is then processed through a five-step flow of analytics to arrive at resourceful insights at the end. The steps of the process are -


Data Collection

There are certain sectors whose services predominantly include a collection of large scale data such as banking, finance, insurance, healthcare, hospitality, transportation, and trade. In this stage, data flows freely between industries to reach their respective vantage points.



Pre-processing is a key stage before the analysis takes place to transform the raw collected data into a meaningful format. It is a data mining technique that makes sense to the inconsistent, incomplete data, cuts down the noise and irrelevancy, and gives them a shape from which further deductions can be made.



Analyzing the processed data includes cleansing, modeling, and evaluating it to arrive at answers to certain questions. But to do that accurately, problems to which solutions are being sought must be determined and questions are to be framed definitively.


Generate Insights

Once the perusal is over, the analysis of the data leads to certain conclusions. These insights are precisely the answer to questions which were posed in the earlier stage and for which the data was particularly processed.


Determine Actions

In the final stage of the procedure, potential business actions are drawn up and suggested to the authoritative body based on the derived insights. Upon accurate processing and analysis of data, the said actions are expected to result in the optimization of business and achieve goals set by the company.

Challenges in Data Analytics

Despite the very streamlined process, the domain of data analytics has been facing quite a few challenges of late. The reason behind it is the complexity and layers involved in each stage. The journey from collection to action is quite a tedious one, and the process itself is quite time and labor-intensive in nature. A number of expert personnel, such as data collectors, data scientists, and data analysts have to come together and collaborate to successfully execute it.

Mining, cleansing, and pre-processing of the data takes up more than 70% of the time and effort of the specialists involved. Quite a large part of it, like data selection, setting parameters, discovering patterns and inferring insights are manual.

As a result, data scientists are impractically expensive to hire, and even then optimization becomes quite an impossibility. That is where Augmented Analytics steps in.

Augmented Analytics: The Automated Future

The challenges faced by data analytics can be combated with the automation of the process flow, which also facilitates a much faster and unbiased one. Augmented Analytics is basically the use of Machine Learning and Natural Language Processing to understand, interpret, and interact with large data sets at a much faster rate and less redundancy.


 Augmented Analytics would speed up the whole process manifold times
 It would do away with the scope of human errors in the mechanical part of the process
 It would bring impartiality into data selection and treatment
 Data scientists and analysts can now entrust machine-operations with the labor-intensive tasks and take upon specialized and sophisticated tasks which require more brainwork
 Analysts can focus more on their own expertise, which is of drawing conclusions and determining courses of action

Choose Outsource2india for Effective Augmented Data Analytics

At Outsource2india, the latest and most refined tools are employed to make sure the best standard of service is rendered to the clients. Augmented Data Analytics is an intrinsic part of what we offer.

Our exclusive services include data mining, data cleaning and processing, data modeling, statistical analysis, and insights generation. Before the ultimate course of action is brought into the picture, this whole procedure is dealt with far more accuracy, precision and swiftness than the regular procedure. As a result, the client's business gets to reap the benefits of the collected data and take appropriate measures with much more constancy than that of rivals.

Contact us if you need augmented data analytics and we will be on our way to help you with the world-class solution.

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