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What is a Data Warehouse in Marketing?

What is a data warehouse (DWH) in marketing?
A data warehouse in marketing provides a central location to store data gathered from various sources and platforms. From a marketing standpoint, this includes all data from your paid ads (Google Ads, Facebook, display, retargeting), CRM (email lists, customer lists), website analytics (Google Analytics, Periscope, server data) and other marketing data. All of the various data sources are extracted, transformed and loaded (ETL) into an aggregated data view to give you a holistic view of your marketing efforts. Essentially, a DWH becomes a business intelligence tool that helps you analyze all your data, understand trends and relationships, and inform strategic decision making. 

What are the main components of a data warehouse?
The average data warehouse consists of four (4) main components: a central database, ETL (extraction, transformation, and loading tools), metadata, and access tools. Your four options for databases are typical relational databases, analytical databases, data warehouse applications, and cloud-based databases. Common access tools include those for query and reporting, application development, data mining, and OLAP. 

What are the types of data warehouses?
There are 3 types of data warehouses: enterprise data warehouse (EDW), operational data store (ODS), and data mart.
EDW is a centralized place where data from all sources and applications of a business are organized and classified by subject. An ODS is refreshed in real time and is used for operational reporting. Data mart is a subset of the data warehouse that focuses specifically on metrics from one department – like marketing. This sets it apart from EDW and ODS because it’s more project-oriented.

What are data warehouse examples?
Let’s take a look at 3 different data warehouse examples.
First up is the basic or single-tier DWH. These types of DWH aim to minimize the volume of data deposited by eliminating redundancy, but won’t suit businesses with complex data requirements or numerous streams of data.
Next is the two-tier or DWH with a staging area. The staging area is a system that “cleans” the data so that only relevant and useful information is stored.
Last is the three-tier DWH or data mart. Data marts add a level of customization by streamlining valuable information needed by certain teams. This means your marketing team receives actionable insights from only the data  they are interested in. 

How do you build a marketing data warehouse?
When it comes to building a data warehouse you first need to answer some basic questions. The first being, “Do we actually need a data warehouse?” If your business (and data volume) is growing, becoming more customer-centric, or google sheets is no longer cutting it – then yes. Next, identify what type of data you want to store, how much storage capacity you need, the type of queries you want executed, and maintenance.

What is the significance of data warehousing in marketing management?
We know that data-driven marketing relies on in-depth analysis of heterogeneous data, but what makes data warehousing so valuable for your marketing management is the streamlining of this process. You’ll often see the phrase “single source of truth” when researching DWH, but it’s not an overstatement. Without a data warehouse, your analysts are having to look at your sources separately (like your CRM and Google analytics) to answer the question, “What happened and why?” With a DWH, all that heterogenous data is cleaned and aggregated to give you one homogenous dashboard that provides you with real time data and actionable insights.

What is marketing data integration?
Simply put, data integration is the process of synthesizing data from all your marketing platforms, softwares, and tools. Integrating this data provides a comprehensive view of your target audience, KPIs, metrics, and conversions.
For each brand, Measured builds an individual marketing data warehouse (MDW) that connects and harmonizes all marketing, commerce, and customer performance data from 275+ available integrated sources. The secure, fully-managed MDW provides brands with a 100% independent data architecture on which they can build sophisticated business intelligence reporting, analytics programming, and data science infrastructure.

 

 

About the author

Madan Bharadwaj

Expert in advertising measurement, attribution and analytics

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