How To Successfully Implement A Data Warehouse

There is a misconception that you only need a data warehouse if you have huge amounts of data. This just isn’t true. Businesses of all sizes can benefit greatly from implementing a data warehouse. However, this will look different depending on the size of your organization and the amount of data and data sources you use. Here is how to successfully implement a data warehouse no matter the size of your business.

Quick Recap: What is a Data Warehouse?

A data warehouse is a central repository for all your company’s data.

What makes a data warehouse different than other kinds of data storage, is that the modern data warehouse can store data from multiple sources, such as your company’s social media accounts, loyalty programs, CRM and ERP software, and even industrial sensors or consumer wearables. This data becomes queryable in real-time, allowing unprecedented access to insights, trends and patterns.

Lately, data warehouses have been moving to the cloud, resulting in a data warehouse solution that is:

  • Easily Scalable

  • More cost effective

  • Quicker to get up and running

  • Optimized for analytics

  • Not resource-intensive

To find out more, check out this Data Warehouse Tutorial or find out more about Data Warehouse Concepts.

Why You Need a Data Warehouse

Being able to make use of a data warehouse can have a tremendous impact on your business in general, and on your role in particular. Adding a Business Intelligence (BI) layer on top of your data warehouse brings about even more possibilities. These include:

1. Identify and take advantages of macro trends

Using your data warehouse to see “the bigger picture”, and figure out the next step for your business. Identify key new product lines, or which geographic market it would make sense to expand to. Find out which products sell best at which locations, or how to optimize your logistics fleet.

2. See patterns in huge amounts of data

Often the sheer volume of data makes it impossible to draw any meaningful conclusions. With a data warehouse and BI tool, you can actually see patterns, and get meaningful information from your data.

3. Find dependencies and correlations

Knowing, for example, that 2 specific products are often purchased together, will allow you to merchandise or bundle these products. In the past, this type of information was based on “gut feel” or anecdotal evidence. With a data warehouse, you can make data-driven decisions and take advantage of patterns, cycles and correlations.

4. Allow different users to query relevant information

The marketing department might want information into sales spikes during the new campaign they’re running, while the engineering team will want to see insights into the efficiency of their new engine design. With a data warehouse, all of these queries can take place simultaneously, in real-time.

5. Have access to standardized data across the organization

By standardizing data – that is, ensuring that all data conforms to a common form – you can now get insights by cross-referencing different types of data. Suddenly, you can lay loyalty program results over help-desk inquiries and figure out ways to preempt bottleneck and identify opportunities.

There is a misconception that data warehouses are only for large companies or enterprises. If your business generates large amounts of data (which any business running a PoS system, an accounting system, or social media campaigns does) and you’d like to look at this data holistically (including gaining insights such as those listed previously), then a data warehouse is for you.

Data Warehouse Project Example

A great example of a data warehouse project is that run by British retailer Tesco. Tesco figured that by matching weather patterns to store performance, they could predict demand at certain times of the day. With massive amounts of data flowing through the system, a data warehouse was needed to handle the project. The results were a resounding success. Tesco was able to adjust the product mix in a particular store, based on weather. For example, Tesco calculated that for every 18F rise in temperature, there would be a 300% increase in barbeque sales. 

Data Warehouse Implementation Steps

Designing a Data Warehouse and setting it up can take mere minutes. Panoply, for example, allows you to add data sources with just a few clicks (catering to almost every data source possible), add a visualization tool, and voilà! You’re ready to go with your very own data warehouse.

Data warehouse architecture will differ depending on your needs. Some companies would want an entirely on-premise solution, however today the vast majority of companies would go for a cloud-based data warehouse. Data warehouse architecture is a fascinating subject, and if you want to delve deeper into this, you can find out here.

Your Data Warehouse Partner

Is a data warehouse for you? It sure is. No matter what size or stage your business, the insights that can be generated from having a data warehouse cannot be overemphasized.

Your partner in getting your data warehouse up and running is Panoply. Panoply is an autonomous data warehouse built for analytics professionals, by analytics professionals.

Get a free consultation with a data architect to see how to build a data warehouse in minutes.
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