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It is expected that companies will invest $92 billion in Big Data by 2026 but will they make a profit of it? If they use the right data discovery approach and focus on actionable insights, they can.

Today, more and more companies are relying on Big Data technologies to answer a variety of business questions that range from resolving company’s strategic management issues to decision making in their everyday operations. But simply gathering big data does not unleash its great potential value. To get the most from it, organizations need to perform big data analysis that can help resolve business issues or capture hidden opportunities. But the truth is that deriving meaningful insights from big data — and converting that knowledge into action — is much easier to say than to do. The accuracy of your analysis may depend on how well you understand the problem and what questions you ask before you start working with a specific dataset.

Wondering how to ask smart questions about big data to get actionable insights that will help you develop an effective business strategy? Keep reading the article to find some easy tips on how to do it right.

Why Do You Need to Ask the Right Data Analysis Questions?

For most companies, the lack of information is not a problem. Actually, it’s the opposite. Often, there is so much information available that organizations feel overwhelmed by it because it is not easy to make a clear decision. Besides, according to American Marketing Association, 90% of stored data will never be used.

Businesses spend millions of dollars on gathering and analyzing information with different data analysis tools but it seems that most decision-makers have trouble actually using that information in actionable and profitable ways. Many C-level executives believe that investing in big data will solve many of their problems. But it’s not a one-size-fits-all issue and first, you need to develop a strong data strategy for your business.

You should keep in mind that no matter how advanced your IT infrastructure is, your data will not give you ready-made solutions for the development of your business unless you ask it specific and relevant questions.

Do you want to transform data sets into business decisions? Identify the pain points you would like to gain insights into before you begin the information gathering process. You should take into account your company’s goals, budget, strategy, and target customers and come up with a set of guiding questions that will help you get relevant insights.

What Questions to Ask When Developing a Big Data Strategy

You are probably collecting a lot of information and you need to maximize its potential:

  • You need to understand if it the right data that can give answers to your questions
  • You need to analyze your information and come to accurate conclusions when interpreting results
  • You need information that will help you make informed business decisions and grow a successful business

In short, your company needs effective data analysis. That’s why you have to begin with the right questions that should be clear, concise, and measurable.

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Here are some useful tips on how to ask questions to get more from your data analysis.

1. What do you want to find out?

You should start by defining your end goals. There is no point in storing huge volumes of information if you don’t have a specific end goal in mind. By specifying the business priorities you want to address, you will be able to focus your efforts on the right kinds of data.

First, you should evaluate how your business is developing so you need to analyze the most relevant KPIs and decide what changes can be made to improve them. Then you should think about specific questions that need to be asked to get the key insights that will help you in decision-making. Next, you should think about the standard KPIs that can be used to measure your data.

 

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2. What are your data sources?

Your next step is to identify your data sources. All the departments of your company can potentially provide valuable insights for the future analysis – sales, IT, finance etc. If you are afraid that the abundance of data sources inside and outside your company can make things too complicated, you should ‘edit’ these sources and get rid of those that are not very meaningful. But keep in mind that the more information is available, the more relevant data you will get. Think what BI platforms you will need to retrieve your valuable data.

3. What should be done to ensure the quality of data?

The point of designing your data analysis questions is to get a clear view of reality to understand what you can do to make your business profitable. And what if your data is not correct? In this case, you will see a distorted view of reality. That’s why you should take care of ‘cleaning’ your data sets to get rid of outdated and wrong information. You should also consider adding more fields to your data to make it more useful and complete.

This job might be time-consuming and even annoying but you will be pleased with its result having a valuable asset of accurate data sets. You will be able to use statistical methods to measure them.

4. How are you going to analyze your information?

You can choose among multiple statistical analysis techniques but here are 3 techniques that are most commonly used for business analysis.

  • Cohort Analysis will allow you to compare various groups or cohort of customers.
  • Regression Analysis is typically based on past data and allows to determine how independent variables influence a dependent variable.
  • Predictive and Prescriptive Analysis allows analyzing historical and current data sets to make predictions on possible outcomes, including risk assessment and alternative scenarios.

There are also other methods that are widely used in data analytics, for example, data mining, seasonal naïve approach, time series, autoregressive integrated moving average, and artificial neural networks. You can choose your method taking into account your resources, skills of your team, and the type of data you have gathered.

5. Who are the end users of your data?

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It’s very important to have a good idea who will use your analysis and how they will apply the reports. You should be aware of their technical skills, needs, expectations, and demands. This information can help you determine what type of data you should focus on and how detailed analytics report will be. Reports may differ for external and internal users because they have different needs.

6. What types of visualization should you choose?

If you want your reports to make a big impact on the target audience, you should take care that they are clean and readable because poor presentation can spoil even the most valuable insights. You will need to convince your company’s decision-makers that your information is important, correct, and urgent to take action upon.

You should be careful when choosing among different charts and graphs to ensure that the information is attractive to the end users and is easy to understand and interpret.

Asking the right data analytics questions, you can optimize your business performance, and set up your company for success. Regular data analysis can help you make important business decisions and motivate your employees to improve their performance.