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The role of a business analyst is changing dramatically in the data science age. Today, you need to become an industry expert, a storyteller and a visualization specialist who drives evidence-based decision making with a human-centric approach.
Ask yourself these questions about your business analyst career:
- Do I have the relevant business analyst skills and competencies to verify the truth in data?
- Can I use the latest machine learning and data virtualization tools to unlock maximum value from a deluge of data?
- Am I solving the right business problem while assessing data?
Business analysts and advisors to data scientists now play a much larger role in a company’s journey to becoming a data-driven, insight-powered business. Gone are the days when you were expected to simply elicit information from stakeholders, analyze requirements and design a solution.
Your ability to understand data, to process it, to extract value from it, to visualize it, to communicate it—that is the next big skill.
The need for data science skills
With an expected 50 billion connected devices by 2020, data is coming at us with an overwhelming velocity. Business leaders are leaning on business analysts to gain accurate, actionable insights that can deliver enhanced customer experiences, new business models, new revenue streams and new ways to grow for every business on the face of the globe.
To spearhead data-driven industry transformation into tomorrow, it’s vital to transform your data science skills today.
4 business analyst skills necessary today:
- Be a business domain expert; stay up-to-date with the latest trends and evolving business models.
Heard about niche targeting, dynamic pricing and drug discovery? As an example, in travel and tourism, airlines are increasingly adopting the dynamic pricing model to come up with highly personalized airfare prices. Based on advanced predictive analytics tools, airlines can propose unique fare structures for each market and each departure day.
Similarly, in the realm of drug discovery, pharma companies are using advanced analytics to flag potential failures and prioritize drugs that are more likely to achieve a high success rate.
Closely following the hottest trends and business models can help you lead companies in making proactive decisions that keep customers at the heart of it all and gain exponential growth.
- Draw insights from data—and intuitively understand the story behind the numbers.
It isn’t information—it’s just data. You need information to isolate actionable insights and make intelligent decisions. Therefore, as a BA in the new age, you must apply your technical prowess and knowledge to convert data into useful information.
Don’t be surprised if the information you gather from an ocean of data talks about an unaddressed market from which you can generate a new revenue stream for your company or client. Even while targeting niche customers, understand what the data is saying, derive insights from it and then analyze what the numbers are conveying.
For example, more than 80 percent of streaming media series for one popular provider are discovered through the platform's recommendation system. The provider uses data as an asset to personalize its content and service to customers.
- Ace visualization.
The ability to create data visualizations used to be one of those “nice-to-have” BA skills. That’s changed. Now that business decisions rely heavily on data, visualization is a must-have skill.
By using some of the best-of-the-breed tools such as Tableau and ClickView, you can slice and dice data to convey a message in the most impactful way.
But before you start, ask yourself—is the information conceptual or data-driven? Are you declaring something or exploring something? Answers to these questions will help you choose the right tools and resources to achieve your goals effectively.
- Be a storyteller and create a narrative inclusive of data.
The need for data storytellers is growing at an unprecedented pace. Businesses want BAs to not just uncover transformative insights, but also to communicate them well to key stakeholders and technology teams.
Remember, it’s not just about finding the business context of the problem, the right technology solution and the various benefits the business will achieve; it’s about building a powerful data narrative. For example, if a company is facing declining sales, you should be able to use your contextual thinking to frame the right set of questions to answer why the company is facing losses. Is it revenue, demographics or lack of skills?
Remember, a data scientist won’t frame the correct business problem. You will.
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It’s about building a powerful data narrative.
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And most importantly, be a true partner and collaborator with all your business and technology teams, who will use your transformative insights to drive outcomes sooner and with greater impact than anyone ever imagined.
Industry domain and package experts are high in demand in the job market right now—and we’re growing our team. Find your fit with us today!
For a deeper look at the way data science can be leveraged to address complex business problems, read the Analysis in the Data Science Age - Driving Industry Transformation whitepaper, developed in collaboration with Accenture.
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