How to Transform Raw Data into Actionable Insights

We live in the world of data, where companies are becoming data business organizations. The future success of most businesses depend on how they effectively analyze, gather, and manage data to reveal insights, which they can use in decision-making. Doing so requires rethinking how to deal with data and how well it fits in digital transformation.

What Raw Data Constitutes in Businesses

In the world of business, you will find different forms of raw data. It can be any record, which businesses collect and store so as to support their operations and processes of decision-making. This data may come in different types, and probably, you might have already started to gather such details, including these:

  • Employee data
  • Operational data
  • Sales & marketing data
  • Customer data
  • Product data
  • Financial data

Challenges Facing Raw Data

Raw data is often complex, creating many challenges in form of quality, format, and structure. Dealing with this complexity is necessary for extracting more meaningful insights, which drive crucial business decisions. Lack of standardization, inaccuracies, and data inconsistency are common issues you may face when managing raw data. By overcoming those challenges, you will ensure reliability of data analysis.

Solving Those Challenges and Transforming Data into Actionable Insights

We all know that data plays an important role in many businesses. But when transforming raw data into insights, you can get stuck a little bit. So, how will you ensure you get the most out of a large data set? Here is how you can do that:

1. Use Power Mining Tool

With raw data, you can deal with inaccuracies and inconsistencies. But power mining tool for power BI can come in handy. It enables users to easily reshape and cleanse data. With this step, you will ensure reliability and accuracy of insights from the data; thus, laying a groundwork to make more informed decisions.

2. Understand Your Audience

To effectively visualize data, it will be important to ensure it intellectually and emotionally resonates with your target audience. So, understanding your target audience is important. It helps to determine preferences of your audience, including language, color, and text size, to name a few.

3. Manage Quality of Data

If you use the same data multiple times, it will be difficult to maintain its quality – that’s the bitter truth we all face. Plus ensuring that your data is consistent, accurate, and up-to-date is more challenging. The best way to deal with that is to check data regularly and use solutions, like data profiling tools.

4. Know the Source of Data

Although quality input is important, it won’t be enough to create an impactful BI output. So, consider the challenges of getting the data on an automated and consistent basis. If it requires manual intervention, first understand how this will affect the value and initiative it’s going to deliver. For instance, if the data is scattered across different Excel files or CSVs, think of what it will take to go to another source instead.

The bottom line is that, actionable insights are key to the future success of businesses. As your company changes and grows, ensure you regularly revisit those insights and data. This way, you will get more insights to make the right business decisions.