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What Are the Different Business Analytics Techniques for Enterprise Managers?

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The global business analytics market is growing at a rapid speed. The major factor driving this growth is the software as a service segment that is also allowing Cloud and Embedded Analytics segments to flourish. According to the major reports published in the recent months, analysts expect the global business analytics market to cross $180 billion in 2030, almost 3 times more than it was in 2020 in the pre-COVID era. Due to the massive demand for great business analytics products, software and Cloud innovation companies are on the constant lookout for some really great talent. These are mostly focused on the areas of software development, data analytics, and business analytics. The toughest part about working in this industry is the widening gap between the skills required to excel in the industry and the actual competencies that the professionals come up with. In order to close this gap, organizations are working in a collaborative manner with leading business analytics courses. These courses are specifically designed to train candidates and experienced workforce in key business analytics techniques—which will discuss in this article.

SWOT Analysis

SWOT analysis or SWOT matrix was developed as part of strategic management and strategic studies of business operations, equating each action on the basis of competitive advantage or disadvantage an organization holds over its competitors or environment. It is one of the most powerful business analysis techniques adopted by millions of business administrators and decision makers in different walks of life. It can be used to solve many different types of complex problems ranging from customization of products to performing competitor analysis for product and market positioning. 

With proper access to data and the right techniques, any analyst can make a huge impact by putting analysis into a concrete action plan.

Situation Analysis

Many companies are now relying on the concept of Game Theory to solve strategic business problems. The use of Predictive Intelligence and Machine Learning tools is highly prevalent in this area of business analytics. This makes situation analysis one of the most advanced and extremely reliable tools to assess and monitor how an organization or team stands up in the face of internal and external challenges and difficulties, and what action plan is ready in time. With the best access to BI tools, analysts are able to accurately predict the outcomes of their decisions in volatile or uncertain times. The manufacturing companies, real estate players, and healthcare management companies are among the biggest users of situation analysis to meet the demands of their respective markets.

OLAP

OLAP is Online Analytical Processing as applied to the various branches of business intelligence domains. In the top business analytics courses, trainers focus on the predictive and descriptive side of OLAP. This essentially refers to the use of advanced and emerging technologies for various types of business analytics techniques. These could be big data intelligence, real-time analytics, predictive analysis, AI-based data visualization, and reporting, and now, search based automated data analysis. Enterprises that invest in OLAP platforms have a limitless scope of scaling their existing BA / BI capabilities, bringing in unmatched accuracy into never seen before data pools. The level of planning that goes into OLAP makes it one of the most extensive business operations in the current scenario, and companies are constantly hiring top analysts to get their BI capabilities to the top. From regression analysis to multi dimensional analysis, OLAP is created to meet “demand” as it comes. This is used in sales forecasting, marketing analysis, employee engagement metrics, and so much more. In fact, by 2030, 40% of the global BA BI software market would be dominated by OLAPs with AI and predictive intelligence capabilities. 

The future of business analytics is very clear and bright. The innovations in the field of business data management, big data intelligence, AI, and deep learning are making working in BA BI fields very exciting. BI teams are leveraging AI assistants and RPA tools to mine, enrich and generate metadata and trained data for advanced machine learning algorithms specifically designed to match the requirements of modern business teams. For example, OLAP cubes are available in different BI tools such as IBM Cognos Analytics which recreates advanced AI features for generating and answering queries, refining filters, and using NLP / NLU to set up conversations with the business analysts. 

There is so much happening in the BI world today. Therefore, certification from a top Business Analytics course makes so much sense.