Netpremacy’s top tips to creating a successful data strategy

11 May 2020

Learn about our 3-step strategy for getting the most out of your data

 

Now more than ever data is becoming one of our most valuable and most governed assets. Data is all around us and it’s something that we are all using to our advantage. Such is our dependency on data and understanding it, we have teams dedicated to analyzing it, understanding it, dissecting it, predicting it…. The list goes on.

The tools at our disposal are endless and the skill set of data scientists and engineers is constantly growing and improving. However, one thing that is often overlooked, and is potentially the most important thing to consider and understand is actually, what do we want to know? And how do we build a strategy to help us get the most out of our data? 

Netpremacy is Google’s 2019 Global Partner of the Year for Work Transformation Enterprise. Our work over the past decade has been dedicated to understanding organisations’ longer-term strategies, understanding what’s driving some of the world’s leading brands, and how data is beginning to play a significant role in this. This ranges from the tools they use for collaboration and innovation all the way to a fully functional data strategy. Our large team of engineers are extremely skilled in the use of Google’s analytics tools and helping identify and build out a longer-term data strategy.

Below are some of our top tips on how to build a data strategy, and what to look out for along the way. 

Step 1: Understand the business & look for a quick success

Before we even begin to look at what new tools we can use, it’s integral we understand what direction the business is going in. 

  • Are we looking to increase online sales by 20%? 
  • Are we looking to enter a new market? 
  • Are we striving for better operational efficiency? 


Once we understand the direction of the business we can identify what we need to know and the questions we want to ask. We’ve found having 4-5 initial use cases or problems to solve builds a good foundation for a proof-of-concept or pilot programme to get started.  

For a lot of organisations, this can be a new concept and something that needs traction within the business, as when done correctly and with complete buy-in from the business, the benefits can be staggering. 

Now we’ve identified the direction of the business, it’s time to choose a problem that can be solved relatively quickly and easily, but will have a big impact on stakeholders across the business. That could be simply understanding buying trends for a specific demographic & building a view of the customer. Once we have a level of trust and success in the business it’s much easier to find new use cases, funding, and momentum to keep the data strategy going. 

Step 2: The Requirements & Governance 

Once the areas where we can have the quickest and immediate impact have been identified, what will really help us gain momentum internally is to understand what data we need:

  • What types of data are we going to capture and work with? Think Structured vs Unstructured, Transactional, or Relational data. 
  • Do we need to augment what we currently have to supplement the analytics we can run? 
  • What sources of data do we have in the organisation?
  • Read our blog on BigData to learn more


Understanding this is key as without the right data and quality the outcomes will be heavily impacted and could make or break any long term data strategy before it gets started.

As mentioned at the start of this blog, data is quickly becoming one of the most governed and controlled assets in the world and with new regulations such as GDPR its integral that we have the correct governance in place. This means truly understanding the data we hold, is it secure? Do we need permission to use it? Who is responsible for it, How do we keep it up to date? 

Step 3 – Skillset and technology

Finally, we understand the strategy of the business, we know what data we have and the governance around it. We can now look at what technology we want to use and who is actually going to use it. Do we have the resource in house? Are we lucky enough to have skilled data engineers waiting for a project to come up and the technical resource to house petabytes of data, query it in seconds, and get an answer? The chances are probably not! But we can work on building the internal capabilities, as there is a significant increase in training courses, qualifications & employees who understand data and can leverage a wealth of different technologies to better gain insights from the data we have

We also need to take into account where this data is going to sit. Do we have the infrastructure to do this all in house? Unlikely! 

This is where cloud providers like Google Cloud come into play. 

As we are looking at housing and querying large quantities of data that are constantly changing and growing, we need the correct environment. We need to be agile, adaptable & make sense of data quickly in order to get the maximum impact across the business. This is why the majority of companies are choosing public clouds such as Google Cloud Platform and using tools like BigQuery to help them. 

We’re lowering IT overheads as we don’t need dedicated local hardware. We don’t need to build our own complex analytics tools. We can simply use the market-leading tools available, make sense of petabytes of data in seconds, and then use this to have a positive impact on the business. 

Sounds simple right? 

These strategies can get extremely complex when we start trying to please everyone, and we need to tread carefully or the use cases will grow and the complexity grows with them. This is where a well thought out and constructed strategy comes in and helps keep us on track.

Netpremacy is uniquely placed to help when it comes to creating data strategies and implementing them. Over the years we’ve understood what makes a successful strategy, built up a team of dedicated engineers who are experienced in Google’s Cloud Platform & have implemented some of the largest data strategies and projects spanning multiple verticals from Retail all the way to Energy & Utilities. 

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