Glossary

Five Questions to Ask Before Diving Into a Data Lake

November 5, 2019  |   Daniella Harkins

My previous post introduced data lakes and set the stage for why brands should consider building a data lake to support their data strategy. As a centralized data warehouse, data lakes allow marketers to aggregate various types of data into one location to drive richer, more predictive analytics. Does this sound exactly like what you need? 

Before committing to this costly investment, here are the top five questions marketers must ask when evaluating the need for a data lake:

  1. How sophisticated is your brand’s data strategy?
    If your brand is newer to managing data or does not have a complex, multifaceted strategy to manage data, then a data lake is probably not right for you—yet. Build up your partnerships and data assets first. Working with a managed service analytics provider may yield quicker, shorter-term results. If your data-driven brand engages with consumers across multiple channels and products, then you should consider a data lake. But again, you must have the right teams and internal structure to maximize value.

  2. Are you a seasoned, multifaceted marketer?
    If your brand uses data to better define its market strategy and collect data from all of your partners, then a data lake might be right for you. The reality is that this decision cannot be made in a vacuum, as you need to evaluate your marketing tech stack. A data lake is a good solution for a strong marketing analytics team. Whether the data lake is a shared enterprise resource or a marketing analytics specific capability should not matter. 
  3. Do you have a data management platform (DMP)?
    Even if you have a
    DMP, a data lake might still be right for you. It depends on what you’re trying to solve for. Remember, a marketing platform and an analytic capability are very different. A DMP is streamlined for marketing use where data is linked and maintained within a platform. A data lake gives users access to, and more control over, deriving insights from data.

  4. What do you want to get out of an analytic strategy that includes a data lake?
    Remember the use case you are trying to achieve. If your focus is tying offline purchase history for media optimization, then working with a DMP will likely suffice. Data lakes are more multifunctional than a DMP and are not only for marketing or media use. If your brand wants to bring more data sets together for stronger analytics and customer insights, then a data lake should be front and center of your strategy. This includes data like consumer product feedback, customer support, consumer touch points, offline data, DM and email promotional data, third-party data, digital media exposure, social listening, and website activity.

  5. Are you looking for a simplified way to manage online and offline data and audiences?
    If you are looking for a streamlined way to manage and activate your data, then a data lake is not the right choice. A data lake is not a marketing tool or platform, rather an enterprise analytics capability that requires heavy lifting and is not usually marketing specific. You should evaluate a campaign management system, onboarder, or CDP and/or DMP, as they are more focused on the ability to streamline and simplify the usage of audience data.  

Marketing really is a game of inches. Those who strive to perfectly curate content across every channel and touch point know they need to take small steps to get further down the field. To do so, marketers need tools that are agile and flexible enough to change the play quickly and effectively. A data lake may help them move closer to that goal.              

Read more on how LiveRamp can work with data lakes to unify, analyze, and activate your cross-channel data.