In order to make the most out of your data you should have a strong strategy accompanied by a good implementation plan. That plan starts with a set of key steps, such as selecting an analytics platform, determining where and if you should warehouse your data, understanding the quality of the data you have, and knowing if you can trust the sources of your data. All of these steps are critical to the successful implementation of your data strategy. We will briefly touch on each of these topics below although each of them is worthy of its own post and we will provide more information in the future. If you are new to data analytics and developing a data strategy for your organization, this will be a good place to start.
How do I choose a data analytics platform?
One of the first decisions you will be faced with is which data analytics platform to choose. There are many platforms on the market today. Let’s start with Microsoft Power BI which is a great option if you are already a Microsoft shop and are utilizing any of the Azure platform tools. Power BI has been adding features monthly and is continually growing the product with fantastic new visualizations and capabilities. We love Power BI, but may be a little biased, since that is what we build all of our reporting and analytics products and solutions on! However, Power BI is not the only game in town, and there are many other options such as Domo, Tableau, Qlik, and a multitude of others. We are often asked the question: Why not just use the reporting and dashboarding tools built into our current solutions like Sage, Procore, and CMiC? Our answer is this: Inevitably you are going to want to generate reports that pull data together from multiple applications into a set of integrated and cohesive reports. And only leveraging individual product reporting capabilities will limit you in being able to see the bigger picture within your data. Using a data analytics platform like Power BI gives you the opportunity to expand and unify your dashboards to cover all of your important data sources and report on the key metrics and KPI’s that are most important across your business.
Should I warehouse my data or bring it directly into the platform?
The next question you might want to ask yourself is where to house your data. Many of the analytics platforms can read data directly from your application of choice (e.g., Procore, Bluebeam, PlanGrid). However, directly integrating your analytics platform to the data source may or may not be the best choice. One important question to ask is whether the data is available directly via plugin or through an integration? Some plugins only expose certain portions of data, whereas an API may provide you broader options to collect all your data. Another thing to consider is how easy it would be to switch dashboarding tools if you ever wanted to change your strategy. If you choose to warehouse your data (e.g., in Azure SQL or Azure Analysis Services) it would be easier to switch to another visualization tool without having to rebuild everything. Overall, it is important to remember that there are many things to consider when deciding how you will integrate your data into your reporting and analytics platform. The key is to start small and take steps to grow into your data strategy over time.
How fresh does my data need to be?
After you decide where to store all your data, you need to decide how current it needs to be. Of course, the pie in the sky answer that it would be best to have real time data, but is that really necessary? For most business cases, data that is refreshed every few hours or even daily will satisfy the end users. As you increase the data refresh frequencies, make sure to consider the limitations you might run into with API rate limiting, processing costs, and support costs. No matter what you decide, you can usually start small and ramp up later, but it is an important factor to consider when you are initially building your solution.
Can you trust your data?
We have all heard the old adage “garbage in, garbage out.” Well, the fact is that nothing could be more true when you are talking about data analytics. It is essential that you trust the data coming into your system in order to make good decisions. This starts all the way at the beginning of your data pipeline at the field operations level where data is collected. It is essential that you build consensus among these teams about how and why you are collecting data as part of your implementation plan. One way to do that is by sharing dashboards with the people who are collecting your data. This will help to show them how the data is being used and the value of it. As the end users start seeing the value of the data, they will begin to improve the quality of their own data entry and push the subcontractors working alongside them. At the beginning, you will likely find you have a lot of incomplete and messy data. However, once your users buy-in and appreciate the value of the data, you will see the quality improve and you can begin trusting that data. As trust in the data grows, so will the use of your reports and dashboards!
As we mentioned earlier, these are just a few things to consider when you are engaging in this work. There is a great deal more to discuss and we will do a deeper dive in future posts. Stay tuned and please, feel free to reach out to us with any questions you may have when you are setting up your data analytics platform.