Paying close attention to your business’s data is a smart way to keep up with the competition and ensure success. However, as the number of data channels and volume of information have steadily increased along with technological advancement, it has become more difficult to keep track of and store information.
Data warehousing is an important aspect of modern business models because of how it improves business development. When data is consolidated into one location it can be easily accessed, analyzed and applied to your business processes. And even though data warehousing has become a common practice for many businesses, there are still some challenges that can be expected during implementation. The following are some of the common data warehousing challenges along with strategies and solutions to help you avoid them.
User Expectation
As more and more information gets added to a data warehouse, management systems have to dig deeper to find and analyze it. This usually means that users expect very refined results from any analysis that occurs. However, it is possible that performance can decrease as data volume increases, leading to reduced speed and efficiency. Manage the expectations of your team so that they aren’t frustrated when this occurs.
Information Driven Analysis
One of the most important aspects of successful data analysis is spending enough time on understanding and documenting your business needs. Because data warehousing is driven by the information you provide, you should map key concepts completely during the early stages of deployment. According to Information Quality Solutions, the better the initial business information model is, the shorter and cheaper your implementation process will be.
Data Structuring and Systems Optimization
The correct processing of data requires structuring it in a way that makes sense for your future operations. As you add more and more information to your warehouse, structuring data becomes increasingly difficult and can slow down the process significantly. In addition, it will become difficult for the system manager to qualify the data for analytics. In terms of systems optimization, it is important to carefully design and configure data analysis tools. This will provide better results, making development decisions easier.
Choosing the Right Type of Warehouse
There is a variety of warehouse types available on the market today, which can make choosing one difficult. Your two basic options are pre-assembled and customized warehouses. Choosing a custom warehouse will save you time building a warehouse from various operational databases, but pre-assembled warehouses save time on initial configuration. Which one you choose will depend on your business model and specific goals.
Balancing Resources
To receive the most benefit from data warehouse deployment, most businesses choose to allow multiple departments to access the system. This can add stress to the warehouse and decrease efficiency. However, implementing access control and security measures can help you balance the usefulness and performance of warehouse systems.
Data Governance and Master Data
One mistake that some businesses make is a lack of investment in data governance and master data. Because information is one of your most important assets, it should be closely monitored. Implementing data governance allows you to clearly define ownership and ensures that shared data is both consistent and accurate.
Data warehousing is an ideal tool to help businesses like yours keep up with changing requirements and data needs. Now that you know some of the key challenges and mistakes associated with data warehouse deployment, you can take steps to avoid them and ensure that your data works for you in a streamlined, efficient manner.
Work With a Trusted Partner
At GlowTouch, we have deep experience and expertise in ETL and data warehousing. Learn more about our data warehousing and ETL services here.
