How to Prepare for Your First Data Warehouse Implementation

Solver corporate data warehouse software example

Data warehousing is an analyst’s dream. Why? All the metrics about the company’s activities is gathered in one place. Well, how do you make that dream a reality? You have to create your first data warehouse. Many software implementations can be challenging, and only a few organizations today achieve successful software implementations on their first try. In this article, we will discuss preparing for a successful data warehouse implementation.

Steps to Implement Data Warehouse Software

You’ve either bought a commercial data warehouse (DW) software or you are planning to build a homegrown data warehouse. Now what?

The first step is to properly plan your Data Warehouse project and architecture. No matter the approach, you will need to determine what data is required based on which questions will be asked by the users at your company when they do reporting and analysis, because the purpose of a DW is to provide company decision-makers with the most accurate, timely information they need to make smart choices. You can do this by aligning your Data Warehouse with your company goals set by your executive management team. This will help your company be on the right track and guide the decisions for where to start.

Now, let’s define a data warehouse. According to Informatica, a Data Warehouse is a “technology that aggregates structured data from one or more sources so that it can be compared and analyzed for greater business intelligence (BI).” Data warehouses are usually utilized to correspond with broad business data to provide greater executive insight into corporate performance. As I first got to know what a Data Warehouse is and does, I wondered how a warehouse is different from a regular database. Well, here’s the low-down. Data Warehouses use a different structure from standard operational databases. Standard operational databases are optimized to maintain strict accuracy of data in the present by quickly updating real-time data. On the other hand, Data Warehouses are designed to give a view of data over time. They exchange transactional volume and instead focus on data aggregation.

Common Mistakes with Data Warehouse Implementation

Here are common reasons found in software implementations that fail:

  • Believing that your DW software will solve your company problems
  • Unclear objectives
  • Trying to use every feature in the new software right away
  • Insufficient training and support
  • Not getting buy-in from employees ahead of time
  • Not planning for change
  • Choosing the wrong software for your company

As mentioned above, because a company utilizes a Data Warehouse solution, it doesn’t mean the software is going to solve all of the organization’s problems. A Data Warehouse software can help fix some of your company problems, but it does not necessarily fix all of them. A BI consultant once told me that a Data Warehouse implementation can be an iterative process, so plan accordingly. Most Data Warehouses are always a work in progress because companies are changing their structures or data sources as well as adding future data sources to their Data Warehouses. Here are three tips the consultant gave me: understand the advantages and disadvantages of using a Data Warehouses, identify your key players early, and make sure security is set up properly.

Data Warehouse Disadvantages and Advantages 

One of the advantages of using a Data Warehouses is that consolidating for organizations with several entities becomes easier as it is stored in one place, and most customization and features are available, such as using attribute rollups and creating a budget/statistical data that resides in the warehouse.

The disadvantage is that the data stored in the warehouse is not “live” data. It will need an Extract, Transform, Load (ETL) process to be set-up and maintained. If your Data Warehouse doesn’t include an ETL tool, I suggest you include budget planning because the Data Warehouse is only as good as the data you put into it.

Identify your Key Players Early

Subject Matter Experts (SME) in the organization because they are the most familiar with the current databases and/or how data is captured. Report writers because these individuals will be generating reports from the Data Warehouse and communicating with SME to determine how the Data Warehouse should be structured and set up. Lastly, database administrators because they can be seen as SMEs as well. Additionally, they update and maintain the Data Warehouse for any changes.

Ensure Data Warehouse Security

Because data lives in one place, the need for security becomes more significant, so employees in your organization aren’t able to see more than they need to, such as payroll.

What important steps in data warehouse implementation are next? Business end users can manage modern commercial Data Warehouses. Configuration and automation of organizational data replication is easy, regardless of whether it is once or on a routine, scheduled basis. Since these BI data stores are Microsoft SQL Server relational databases, organized by subject, like customers, products, and sales, you often don’t have to involve IT for day to day management of the data. Data Warehouses offer cross-module analytical and financial consolidation functionality because they house diverse data types from disparate sources.

Standing on their own, they usually don’t require transactional processes, concurrency control mechanisms or recovery, besides the database backup. Commercial Data Warehouses, as compared to homegrown DWs, come with pre-built business functionality, such as eliminations, currency conversion, data cleansing, and integration techniques to make your processes more efficient and powerful. You can also use a Data Warehouse to help in the migration of data from an old accounting system to your current enterprise resource planning (ERP) system. Rather than converting years of historical data over to your ERP, you can actually store this information into your DW and do your historical analysis from there, just bring over to your ERP, for instance, the last period’s closing balances.

Why Choose the Solver Data Warehouse Software Solution?

Data Warehouses will continue to become more popular, especially since you can bring multiple data sources into one place to improve your budgets, data visualizations, and financial reports. If you would like to rely on one platform to consolidate your data and any other information for other data sources, without depending on IT to manage the software, commercial DWs can provide you that kind of solution. I suggest companies don’t start building a homegrown Data Warehouse without first looking at investing in a commercial DW from vendors of products such as Solver, Teradata, and Redshift among others.

In closing, poor decision-making, combined with inadequate BI and Corporate Performance Management (CPM) solutions, will lead to an organization’s downfall. Consider what your company needs regarding a Data Warehouse and ask yourself if your company is capable of experience and maintaining the software implementation that your company has chosen. With these ideas in mind, it should give your company a clearer direction in implementing your first Data Warehouse tool. I suggest you communicate your company goals to your consultant or a DW architect.

Solver enables world-class decisions with Solver, a leading web-based CPM suite made up of budgeting, reporting, dashboards, and data warehousing, delivered through a web portal. Solver is reinventing CPM with its next-generation solution. Solver empowers business users with modern features including innovative use of Excel in the model design process. If you’re interested in learning more, our team is excited to hear about your organizational needs and goals.