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Asking the Right Questions through Big Data

Using Big Data to ask the right business questions

The data you collect has a lot of value and carries with it the potential to improve the performance of your organisation. It can reveal insights that lead to opportunities, help you spot trends, solve problems, and enhance operations, among many others. This is the very reason why more and more companies are now embracing Big Data.

The key is proper data analysis. With so much data at our disposal, it’s how we use it that really counts. Decision-making, problem-solving, and business improvement and development all rely on the right questions and answers, which Big Data can help you ask and find.

The Importance of the Right Questions

You may ask questions all the time in your business practices. What price offers the best margin? How will certain factors impact operations? Do I need to venture out to new products and services?  Answering questions like these allows organisations to be agile, reacting better and more quickly to internal and external circumstances. But it’s the questions you aren’t asking that may have the ability to expose more options and avenues that offer success and solutions.

It’s not just about effective problem-solving at this point. Being able to ask informed questions uncovers a more holistic view of your entire enterprise. Through Big Data analysis, you’ll be able to decipher the right questions to ask to know how you can help your business flourish and save you from wasting time going down the wrong or unproductive path.

Finding the Right Questions

According to data analysis expert Roy Wilds, “the combination of Big Data and modern data science can empower you to ask questions in entirely new ways,” and moving from descriptive analytics to predictive analytics (or combining the two) and finding similarities in data found after analysis is a good start. You’re bound to find clues such as data relationships and patterns towards addressing an issue, improving operations, or solving a problem. If you follow them, you will find something useful.

In the landscape of data analysis, most organisations are using data-based concepts. The data requirements for an application create the data model, consisting of entity types, attributes, rules, relationships, parameters, and the definitions of all these elements. Using data-based concepts, the questions users may ask are almost pre-determined.

For example, if you’re an HR manager and your data model consists of a variety of attributes about company employees, you may ask questions that tie back to this data such as “What’s the average salary?” or “How many years of experience do our employees have on average?” These are simple questions that provide information that’s helpful but probably not really transformative or ground-breaking. However, if you looked at all your personnel data as a whole and started to see patterns around employee reviews and retention, you might start to ask questions like, “What’s the correlation between high reviews and retention?” or “Do review scores begin to fall after an employee has been with the company a certain number or years?”

The last two questions are more meaningful and, when answered, offer more than just stats and figures—they can be the start of a path towards positive business-wide changes such as better employee performance review systems and improved employee retention plans.

The good news is, this idea holds true no matter the industry you’re in. All businesses, even the most successful ones, can still benefit from asking the right questions. After all, you can’t get to the answers without questions, and the quality of the answers you’ll get depend on how good your questions are, and how you ask them. Proper data analysis enhances your capability to ask questions that matter more and will have a significant effect on business.

Dutch Wireless Carrier Asks Key Questions from Data

Vodafone Netherlands is a global wireless carrier that found great advantages in asking the right questions based on data acquired. The company began to understand the value of non-traditional customer-based data such as social media posts and web browser history. By adding this data to more traditional consumer data such as user preferences and demographics, the company was able to gain more insights leading to the right questions in terms of marketing to their audience better, which they were able to do.

This has led to successful marketing campaigns. Vodafone didn’t just stumble upon these nuggets of wisdom—they began to see there were holes in the buyer profiles and began to ask, “Where can we find the right data on consumer preferences?” The answer was in the streams of non-traditional data they had.

Big Data Yields Answers

You just can’t ignore the possible goldmine of information hidden in your data that could offer new ways to maximise opportunities and the ability to make optimal changes. To get to this place, you’ll need the right data analysis tool that’s able to effectively analyse and translate data into actionable insights. Latize’s intuitive data management platform Ulysses harmonises internal and external data, allowing you to connect the dots and ask the right questions towards taking your business to the next level. Contact us today and learn how we can help you make the most out of your data.

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