How to build a business strategy around big data

Author Nina Tudor
Category Technology
Date Jun 17, 2020
5 min read

Just collecting data isn’t enough. For it to be efficient, you need to be able to incorporate it into your strategy. And that’s what this article is all about — helping you build a business strategy that’s focused on big data.

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Depending on your business strategy — gathering, processing and visualization of data can help your company extract value and financial benefits from it. Our new ebook will help you understand how each of these aspects work when implemented both on their own, as well as when they’re linked together. Download it for free!
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In our previous blogs, we talked about specific aspects of data gathering, processing and visualization, and now we are ready to utilize big data as a way of building a business strategy by turning it into an integral part of the company.

When it comes to building a business strategy around big data, it seems logical to start with gathering and move to the visualization aspect, but going the other way round is actually more efficient.

You want your goals to guide your process, so you should start by defining the results you want to get — pinpoint what you’re trying to achieve with big data, and then move onto the aspects that tackle the question of how you’ll analyze collected data and where you’ll gather that specific data you’ll need to achieve set results.

Here’s how that process works!

The step-by-step process of building a big data strategy

Step #1: Align your business strategies and goals with data

Understanding and defining your company’s key business initiatives and goals you want to achieve with the help of data is the key to being able to go through all of the other steps on this list and identifying use cases, analytics, data, big data architecture and tech requirements.

As for specific tactics — invest your time to envision the final results you want to achieve. The best way to do it is to answer this question: ‘if I were to combine high volumes of data with advanced analytics, what kind of output would provide the most value to my company or users’.

Be as detailed as you can in your answers, as they will guide you through all of the following steps.

Step #2: Identify use cases and determine the economic value of data

Once you have defined your goals, you need to validate them by creating and testing use cases.

Your objective is to determine if the result you envisioned in the first step is actually achievable through big data and if the output you’ll end up with will actually provide value to your company and users.

If the answer is yes, you should then proceed with determining the economic value of data — the easiest way to do it is to determine a financial value for all of the benefits your company can gain from implementing data.

Step #3: Define your main data analytics models

This step is all about determining your analytics models that will be used for data optimization, predictions, data visualization and decision-making.

This is where you need to specify how the models will create additional business value, how will they be used and who will use them.

In this step, it’s important that your company sets up specific requirements based on your defined use cases to ensure that you gather and process only relevant data, as everything else will only waste your resources without providing value.

Step #4: Define the tools and technologies

The next step is to determine the tools and technologies you’ll need.

You need to create a list of features your ideal solution needs to have in order to provide you with the most efficient way to get from raw data to results you set in step 1.

Depending on your business strategy and goals, you might be able to get an off-the-shelf solution for data gathering, processing and visualization (or any single one of those aspects), but in most cases, you’ll need a custom solution that can cover the specifics of your strategy and easily implement into your business.

Step #5: Map your primary data sources

The final step before you actually start building your data system is to define the main sources from which you’ll gather data. Yes, having more data is usually better, but only if you can use that data.

Gathering giant sets of data just to have them collect dust somewhere on the servers is an extreme waste of resources, so focus just on what’s important and what will ultimately provide your company or users with value.

While identifying your sources, always keep in mind the main outputs you want to get and the processing model you plan on implementing — they will help you guide your choices.

Step #6: Build your company’s big data capabilities

After you’ve completed all of the previous steps, it’s finally time to start building your company’s capabilities for gathering, processing and presenting data — depending on your business strategy and goals you set, you may need to cover all 3 of these aspects or just some of them.

This step consists of hiring a team of data experts and/or building custom tools and applications that will enable you to handle and automate the process of data gathering, processing and visualization.

Once your custom data system is live and operational, it’s all about testing, optimizing and iterating it — that way you’ll ensure that the system is always providing your company or users with the maximum possible value.

Let us introduce you to the world of Big Data

If everything you just read here, or in any previous blog posts, sparks your interest, contact us for more information about how we could help you in making your business more data-oriented. However, if you think that you need to learn more about big data before talking business, we invite you to download our free ebook about the value of data where you’ll learn what exactly is big data and how to monetize it, as well as how it will change and evolve in the near future.

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