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In 2020, more than 3 quintillion bytes of data were generated and analyzed per day. A large percentage of data has been lost already forever due to a lack of enough resources, talent, and technologies. Data scientists and top leaders understand this challenge very well, and therefore, 93% of these leaders have begun to tap top talent from leading business analyst courses to work in Big Data Project Management.

In this article, I will explain how business analytics works in real-time and why you should pursue a career as a business analyst when data science, strategic planning, and automation are at crossroads in the enterprise software development market.

Understanding the Basics of Business Analysis in 2021

In the current market scenario, almost every organization can be considered as a data enterprise, working with Big Data in the form of internal employees and documents management systems, or collecting data from external sources, largely pertaining to customer data or competitor data. Irrespective of what is the source of any data, the real understanding of working with these data is what makes the current business analysis market so complex. There are at least two different types of data outcomes available from the same source. And, it’s the job of a business analyst to present the true picture of how this information can be accurately and most judiciously used to decide the future of any effort taken to sustain a business.

Modern business analysis is an extension of computing and decision-making sciences that enable decision making groups in the company to plan strategic goals and roadmaps for organizational development and market expansion. At the core level, every organization is driven by one key goal – profit maximization. However, in the internet era, with the rise of the global village concept and co-competition across industries, we are witnessing a seismic shift toward the use of business analysis for more than just developing profit maximization tactics.

Tools and Techniques used to Crack Complex Business Problems in Real time

Today, business groups are using business analysis to develop internal communication channels, automate customer service contact center agencies, re-engineer supply chain management, and much more around dynamic concepts of Customer Experience Management and Digital Transformation. Together, the CX and DX part of the business takes business analysis to a place where mere certification in the business analyst course wouldn’t help. You need to tackle complex business problems using human intelligence, augmented by Artificial Intelligence and Machine Learning, ably supported by Robotic Process Automation, Document Processing, and NLPs.

There are many tools and techniques available in the market for you to evaluate and expand your understanding of business analysis. We will focus on the best that makes learning data science worthy in the current context.

The first is Business Model Canvas.

Developed in 2005, you can see BMC is a very new concept and designed extensively for the startups economy where the scale and reach of any new business are exponential. With so many players vouching for market share in a small frame of time, it becomes extremely important for a business analyst group to understand the value proposition, customer relationship, cost structure, and distribution channels. You need a data visualization channel to proactively run with BMC models.

In short, it’s time for a business analyst to contribute directly to revenue generation streams using automation, and digital workforce management. This can be seen in emerging industries such as digital wallets management, international cross-border payments, AI development, IT modernization, and so on. The industries that are still lacking co-development plans for business analysis are lagging behind, risking employment opportunities as well as profit maximization goal posts.

The second is event storming, which is used in Software domain drive designing, also called S3D. It facilitates the agile part in IT and DevOps and therefore becomes very important from a business analysis perspective in a data science market. You can see how the IBM software team uses S3D in event storming techniques with predictive insights generated from highly advanced AI ML models for data analysis and data visualization. In fact, it’s the event storming technique concept that has been picked across the data science industry for designing various customer relationship models, that we know as journey mapping, sentiment mapping, 360 degree marketing analysis, and persona development for omnichannel marketing. It is also used to design campaigns in email marketing and social media management.

Now, you can handle all the critical aspects of project management, supported by Machine Learning and data analysis.


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