Data Warehouses: Why a Single Source of Truth Is Necessary for Customer Analysis

Over the years, companies have managed to collect a large amount of user data. However, that data is rendered useless without analysis that derives actionable insights. Jeremy Levy, CEO and Co-Founder of Indicative, shares the various ways analysis of a company’s data warehouse helps product teams make more efficient decisions. 

As the recent Snowflake IPO demonstrated, cloud data warehouses (CDWs) are increasingly necessary for the era of data. Companies have collected immense quantities of user data for years, but that data does little good without actionable insights. Customer analysis of the data stored in a company’s data warehouse helps product and marketing teams make better, more informed decisions. 

Product teams seek to understand the customer’s journey and prepare features that will better engage users. Growth marketers work to determine the optimal conversion pathOpens a new window and identify the highest-value customers. Easily accessible analysis that yields answers to those questions can transform a company’s thinking. Crucially, that analysis must be built upon a solid foundation, a single source of truthOpens a new window to which all departments refer. 

Enter the data warehouse — an organized central repository for all user data. Drawing analysis from a CDW provides various benefits for your company.

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Depth and Speed of Analysis

Perhaps the best reason to set up a CDW for analysis is the sheer volume of business questions you can answer. Having well-organized data — and a single source of truth — is a prerequisite for analysis. Once companies can see the customer journey through every touchpoint, each department has new insights to integrate into their decision-making. Your product team sees an optimized product roadmap, and your marketing team sees the ideal customer and how they arrived. Data analysts can turn their attention to overarching questions beyond the day-to-day.

Traditional business intelligence (BI) tools like Looker and Tableau connect to data warehouses and help companies understand what has happened over the course of a day, week, or quarter, but are constrained by the limits of SQL. These tools may get you the “what”, but to get to the “why” and “how” of your user data, look to a dedicated customer analytics platformOpens a new window . In-depth customer analytics for product and growth marketing teams bypass the need for SQL queries, making analysis easy for nontechnical users and drastically speeding up the process.

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Clean, Error-Free Data

Data is only as useful as it is accurate, and data duplication introduces a number of opportunities for errors or inconsistencies to enter into your data. It is critical that everyone in an organization is referring to the same source of truth rather than employing multiple methods to track the same behavior. 

For different teams to glean useful analysis from user data, the best solution is to park that data in a data warehouse and connect any additional analytics or business intelligence tools directly to the source. Data warehouses also facilitate the preparation of clean data, increasing consistency in internal reporting by standardizing, and centralizing the data handled by different departments.

Without a data warehouse, using multiple systems that have different sources of truth, it can be difficult to protect the integrity of user data; and running analysis on incorrect, incomplete, or different data is simply a waste of time and resources.

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A Future-Proof Data Stack

Over the last several years, it has gotten much easier for a company to build its own data warehouse, with turnkey options from Amazon, Google, and more. CDWs are designed to scale rapidly to keep up with a growing volume of user data, and cloud-native solutions in your data stack will unlock better performance when compared to legacy on-prem systems. 

New technologies will emerge within space. Mergers and acquisitions like Twilio’s purchase of SegmentOpens a new window will reshape the data stack. The best thing you can do to future-proof your data stack is to control your structured data at a fundamental level, so whatever new products hit the market over the next decade, your company’s data is ready to go. Cloud data warehouses scale to meet the needs of your business without needing to make significant adjustments to your technical infrastructure. 

The advent of cheap and accessible data warehousing has paved the way for an analytical revolution. With every passing year, the cost of building and operating a data warehouse has decreased, and the value a company can derive from data analysis continues to increase. Once your company is collecting user data into an organized data warehouse, all sorts of new possibilities are open. 

Product and marketing teams can act on sound data rather than instinct. Structured data in your warehouse can interface with new and emerging technologies, preventing the need to reconstruct the wheel. Extracting valuable insights from within user data makes companies smarter, products better, and customers happier.

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