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Why AI Is (And Has Been) the Next Big Thing in Data Analytics

Publication date: 14 September 2021

Modern business processes are characterized by a high level of complexity involving tasks that are too stressful to be carried out efficiently by humans. At least, mostly by humans. With the help of AI solutions, notably through AI-driven analytics, businesses can thrive and maintain relevance within the fierce competition. 

As a result of AI, data analysis has advanced significantly in recent years

Predefined dashboards, manual data exploration, and insights reserved for a small group of data experts are a thing of the past. With augmented analytics, insights tailored to users’ needs are available to anyone in an organization in a matter of clicks.

AI-driven analytics, also known as augmented analytics, aids in discovering hidden patterns in large data sets and the discovery of trends and actionable insights by leveraging analytics, Machine Learning, and Natural Language Generation.

But, what does all of this mean for your business?

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Why AI Is Still King

It Has Numerous Advantages

By gathering and processing data, business intelligence can assist in making better business decisions and driving higher ROI. A good BI tool gathers critical data from internal and external sources and provides actionable insights.

Simply put, augmented analytics improves business intelligence and assists enterprises by:

  • accelerating data preparation, 
  • automating insight generation, 
  • allowing data querying, 
  • empowering everyone to use analytics products, and 
  • automating report generation and dissemination.

Automation Rules the Game

The main issue with traditional data analysis is the time-consuming process required for data analysts to extract and clean their data. 

By automating the ETL (extract, transform, and load) data process and providing valuable data that can be used for analysis in a matter of seconds, augmented analytics eliminates this obstacle.

Once the data has been prepared and is ready to be processed, augmented analytics employs machine learning algorithms to automate analyses and generate insights quickly (which would take days and months if done by data scientists and analysts).

Simplification Always Wins

Furthermore, augmented analytics makes it simple for users to interact with data by transforming data analytics into a two-way conversation in which businesses can ask questions about their data and receive real-time answers. 

This is possible with the help of NLQ and NLG because software takes in natural language queries, translates them into machine language, and then produces meaningful results and insights in easy-to-understand language.

The querying data feature allows professionals to delve deeper into their data. More importantly, it allows everyone in the organization to use analytics products, allowing businesses to no longer rely on data scientists or professionals with technical expertise to analyze data using BI tools.

Is your business utilizing data analytics properly? At HICO-Group, we offer a holistic approach to customer solutions for business intelligence. Our team of BI experts can help you make the most out of your data analytics efforts or set up a custom BI solution for your company that meets the needs of your business and market.

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