10 Reasons to Unify Your Data With a Data Warehouse

Savvy leaders are transforming their organizations with data, using hard numbers to make decisions and align their teams toward tangible goals. More efficiency, faster production, lower costs — all of these are within reach for organizations that can master their data.

As more and more tools are required to drive different processes, and each provides different sets of data, the key is to manage and govern increasingly massive data collections. For hundreds of thousands of companies, that means unifying that data inside of a data warehouse.

What is a Data Warehouse?

A data warehouse is NOT just another database. A data warehouse is a federated (uses a unifying standard for separate databases) repository for all the data collected by an enterprise’s various operational systems. Data warehousing emphasizes the capture of data from diverse sources specifically for access and analysis, including large-scale analysis, rather than for transaction processing.

Because they’re designed for analytical processing, data warehouses offer many advantages for organizations of all types.

Benefits of Unifying Your Data in a Data Warehouse

1. More Consistency in Your Data

A properly deployed data warehouse makes it possible to convert data from many different sources into a unified format. Once in the data warehouse, in the standard format, all of your analysts, throughout various departments and teams can access the data in a governed, standard, secure way. This allows you to keep processes standardized and consistent across the organization — while still providing analysts all the data they want and need.

2. 360 Degree Analysis

Data warehouses are designed specifically to aggregate data from many sources into a specifically accessible central store. By unifying the data in one place, (and in the same format) analysts can perform more comprehensive, 360 degree reviews. You get both deeper and broader analysis on all the trends happening throughout your company.

3. Better Organizational Alignment

With better 360 degree insights and different teams (sales, marketing, operations, support, etc.) all using the same repository for reporting, each department can better align with the others. All the key stakeholders can see what’s going on throughout the organization and stay on the same page. The practical implications extend beyond analysis and directly into day-to-day operations: the left hand can always know what the right hand is doing and take action in concert.

4. Built for Performance

Data warehouses are built differently than operational database systems, which are more focused on creating and modifying data. Data warehouses are built specifically for analysis and retrieval rather than the upkeep of individual records. As a result, they offer both a more scalable solution for storing large volumes of data and faster processing for advanced data analysis using BI tools, processing queries more efficiently to enable faster analysis.

5. Simplify API Management

Data warehouses help eliminate API management headaches. With data warehouses, there’s no need to juggle or manage separate APIs to access data in every single application or database. Instead, you simply copy the data from a given data source and replicate it in your data warehouse, saving time and reducing error-prone processes. Then, you can use transactional replication, which copies only new entries in the data source to the data warehouse, so your warehouse stays up to date without a massive stream of new data eating up bandwidth.

6. Skip the API Limitations

Another benefit of using data replication is that you circumvent costly, complex API limitations. This expands your general data access by allowing you to dodge the problems associated with live querying of certain APIs that are either slow or limit the number of queries you can run against them.

7. Historical Intelligence

Data warehouses can store absolutely gargantuan amounts of historical data, with some organizations’ data warehouses clocking in at petabytes of data. For context, a petabyte is 1000 terabytes, or 1 million gigabytes, the unit most people use to denominate storage needs. With spacious petabytes of data at your disposal, you have all the elbow room you need to track historical data, giving your organization the ability to analyze different time periods and trends in order to make future predictions. This is crucial because vast reams of historical data just can’t be stored in a transactional database or used to generate reports from a transactional system — databases get too cumbersome and quickly overloaded.

8. 167% Median ROI Due to Massive Cost Savings

According to an in-depth study conducted by the International Data Corporation (IDC), the median three-year ROI of a data warehouse investment was 167 percent, for a wide range of companies studied, big and small, across industries. The average was even higher, at 400 percent ROI. The reason? Data warehouses help organizations massively cut their costs for streamlining and governing their data. Organizations that start with an actionable path and iterative, smaller projects can especially speed up their payback period, with the average payback period at just over 1.5 years.

9. Proven and De-Risked

Enterprise data warehouses have been around forever. The military command-and-control, intelligence, manufacturing, banking, finance and retail industries have used data warehouses since the 1960s. In the mid-90s, data warehousing emerged as an IT specialization, after Walmart changed the game. Behind the mastery of Walmart’s supply chain, their data warehouse helped them leverage transaction data collected by its point-of-sales systems to gain deep insight into the purchasing habits of its 100 million customers and the logistics guiding its 25,000 suppliers. Since then, data warehousing has steadily gained adoption by many of the biggest companies in the world, with proven implementation models.

And on the actual data warehouse side, you’re dealing with the hulking giants of tech: Amazon, IBM, Microsoft, Oracle, Google and Teradata (which has been around for 30 years) provide the largest data warehouses on the web, all with deep support.

10. Higher Security: Consolidated Data Access

By using a data warehouse as a unified repository for your data, you can not only bring together all your data, you can make it more secure through consolidated data access. If you control data access through a centralized system, you can combine role-based user access controls, providing different permissions to different users, with row-level access controls (which data is available to different users) to lock down data security. In particular, row-level access control provides several security benefits, including:

• More granular data security: set permissions for rows, not just tables and columns
• Automatic data filtering according to group, role, application and more
• Server-encoded data-level security

This helps meet compliance requirements for regulated industries, such as healthcare and comes standard now in the biggest data warehousing tools.

How to Move Data into Data Warehouses

There are a number of different ways you can get data from your various enterprise IT systems, databases and applications into a unified data warehouse. One that is particularly effective for this type of use case and gets around many integration challenges and API limits as well is incremental data replication. In this process, you use a tool to replicate data from various sources into the warehouse then regularly sync new updates (or increments) from those sources into the warehouse.