Choosing between a customer data platform vs. data lake solution? Data lakes are powerful data storage solutions that can store massive quantities and varieties of raw information. Customer data platforms ingest customer data from a variety of channels and centralize it for quick access, analysis, and activation. Which choice is best for your customer data initiative? First, let’s define these two solutions clearly before we dive into more specifics. 

Customer Data Platform vs. Data Lake

Data lakes are centralized repositories capable of storing large amounts of structured and unstructured data in their raw form. These raw files are usually associated with metadata tags and other identifiers for future use. 

Customer data platforms are defined by CDP.com as: “A CDP is a software package that consists of a centralized database with the ability to collect, manage and activate data from multiple sources in order to affect the digital customer experience (CX).”

Below are some key differences between the two:

Storing Raw Data: Customer Data Platforms vs. Data Lakes

To decide which solution will work best for your needs, first ask what data you need to store and why you will use it. Data lakes can take in massive amounts of raw data ranging from unstructured information, like random collections of images, text, etc., to structured database rows. 

CDPs also take in large amounts of data, typically as first-party information or data collected from primary business channels like websites, mobile devices, POS systems, and others. CDPs ingest streaming, real-time, and historical data from these sources as well as information from second- and third-party sources. This effectively eliminates silos by centralizing data collection and storage for all users.

One key difference is that data lakes store data in their raw state, whereas CDPs automate ingestion with rules for quality and governance. This means data lakes require data scientists and engineers to prepare data for analysis by cleaning and deduplicating it. In contrast, CDPs offer non-tech users cleaned and enriched datasets for analysis without excessive reliance on IT teams.

Creating Analyses

As mentioned above, CDP offers ready-to-use data for analysis while data lakes only offer raw information that requires preparation in order to perform any analyses. This means data lakes can slow down decision-making when sales and marketing teams must wait for data sets to be processed. On the other hand, CDPs enable real-time analyses of customer data to deliver timely insights for sales and marketing teams. 

Another key difference is that CDPs come with built-in connectors for integration with a range of analytical marketing and business tools. This makes CDP a plug-and-play solution compared to a data lake, which lacks out-of-the-box integration or connectors.

Making Actionable Marketing Plans

A ton of data won’t make a marketing campaign effective on its own, but the ability to draw insights and apply them in actionable ways will definitely make an impact. Here again, a data lake’s business value ends with the capability to store a wider range of raw information. In contrast, a CDP can ingest, process, and analyze data to draw real-time insights to fuel actionable marketing plans. Using such consumer insights, marketers can quickly spot trends in business trends and take immediate action. 

Another key consideration is that CDP users are able to drill down to more specific audience segments and draw deeper, nuanced insights more frequently than data lake users. This deeper customer understanding allows teams to seize critical moments in the buyer’s journey and achieve marketing/sales goals with greater accuracy. Floating insights from a data lake take time and effort, hampering teams from pivoting quickly in critical conversion moments.  

Still undecided about customer data platforms vs. data lakes? At the end of the day, CDPs offer a more robust data storage solution and facilitate data activation. Data lakes—while useful as a repository for a wide range of raw information—ultimately require a range of external martech tools to bring business value to a stack of static data.They also lag behind CDPs for drawing insights quickly from raw data, because data scientists and engineers must perform data preparation, modeling, and analysis before delivering insights. Because CDPs come with these capabilities out-of-the-box (i.e., data quality and governance, segmentation, and analytics), they empower non-tech marketing and sales teams to make quick, data-driven decisions based on real-time insights. 

Upgrade To A Customer Data Platform

Enjoy the benefits of Treasure Data’s best-in-breed Customer Data Platform:

• One platform to store all streaming, real-time, and historical data
• Automated and schemaless ingestion of event-level data
• Advanced predictive analytics powered by Artificial Intelligence and Machine Learning
• Audience and campaign activation with a click
• 170+ built-in connectors and integrations 

Treasure Data’s cross-functionality eliminates the need for multiple tools to store, clean, and track data. Our powerful customer data platform takes care of data preparation so sales and marketing teams can perform analyses on the go. Global businesses use Treasure Data to track consumer trends quickly and make winning, data-driven decisions in an ever-changing business environment. 

To learn more about the benefits of a customer data platform vs. data lakes, consult an expert today. Want to learn more? Request a demo, call 1.866.899.5386, or contact us for more information.