Augmented Analytics and Modern Business Intelligence Adoption to Maximize Business Value

Abstract

The business success is critical for any organization irrespective of its size. Understanding business value and advanced technology capabilities in Business Intelligence (BI) solutions for analysis and decision making is the need of every management, researchers and analysts. Data is available at every corner, at every platform and it is being produced all the way using digital equipment. These complex data sets for analysis and decision-making can be used on various platforms and are more accessible than ever to find insights and explanations. There is an abundance of datasets and data analysts, but organizations are still unable to leverage its potential to the fullest and this perhaps is the failure of most data analytics initiatives. This paper covers the need for Augmented Analytics adoption in companies to maximize business value with respect to added advanced analytics capabilities in BI Tools for effective, accurate and timely decision making, and business analysis.

Augmented Analytics Driven by AI: A Digital Transformation beyond Business Intelligence

“…In other words, it acts like a virtual data scientist who executes analysis activities and operationalizes data findings [ 2 ]. Thus, leveraging the full potential of AA features makes analytics accessible and easier to use, resulting in more data-driven and timely decision-making for overall organizational growth [ 3 ].…”

“…Furthermore, AA supports natural language and conversational interfaces that enable users to run text and voice queries [ 4 ]. Moreover, it provides business users with unbiased data analysis, highlights unknown growth opportunities, and supports agile enterprises [ 3 ]. In addition, it improves the utilization of resources, as data analysts can focus on the more difficult tasks that cannot be fully automated.…”

“…The analyst may use NLP to ask questions and find answers in the form of visuals that may help in finding insights. Consequently, intelligent visualization and interactive dashboards with storytelling are used to share findings from the data, with the support of collaboration capabilities to show patterns and hidden insights [ 1 , 3 ].…”

“…In addition, Deep Learning (DL) has begun to be considered as an added value for BI platforms in the market [ 8 ]. A new approach was introduced by Gartner in 2017 that incorporates BI and advanced analytics such as AA and is expected to be the future of big data and analytics [ 3 ].…”

“…It also reduces the cost of cleaning and reporting data because it utilizes AI and ML to computerize many processes. Furthermore, AA platforms solve complex business-related problems and help accelerate decision-making for managers and improve the quality of decisions [ 3 ]. Table 1 shows some of the expanded capabilities of AA compared to BI [ 8 ].…”