This article will focus on the process of preparing for a successful data warehouse implementation.
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? First, you have to prepare for your data warehouse implementation. 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 DW implementation.
You’ve either bought a commercial data warehouse (DW) software or you are planning to build a homegrown DW. Now what? The first step is to properly plan your DW 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 DW 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 (DW). According to Informatica, a DW 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).” DWs 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 DW is and does, I wondered how a DW is different from a regular database. Well, here’s the low-down. DWs 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, DWs are designed to give a view of data over time. They exchange transactional volume and instead focus on data aggregation.
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, and finally, choosing the wrong software for your company.
As mentioned above, because a company utilizes a DW solution, it doesn’t mean the software is going to solve all of the organization’s problems. A DW 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 DW implementation can be an iterative process, so plan accordingly. Most DWs are always a work in progress because companies are changing their structures or data sources as well as adding future data sources to their DWs. Here are three tips the consultant gave me: understand the advantages and disadvantages of using a DW, identify your key players early, and make sure security is set up properly.
Advantages/Disadvantages of DW: One of the advantages of using a DW 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 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 DW doesn’t include an ETL tool, I suggest you include budget planning because the DW 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 DW and communicating with SME to determine how the DW should be structured and set up. Lastly, database administrators because they can be seen as SMEs as well. Additionally, they update and maintain the DW for any changes.
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’s next after implementation? Business end users can manage modern commercial DWs. 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. DWs 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 DWs, as compared to home grown 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 DW 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.
DWs 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 DW without first looking at investing in a commercial DW from vendors of products such as BI360 Data Warehouse, Teradata, and Redshift among others.
In closing, poor decision-making, combined with inadequate BI solutions, will lead to an organization’s downfall. Consider what your company needs regarding a DW 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 DW tool. I suggest you communicate your company goals to your consultant or a DW architect.
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