Why You Need a Data Warehouse: What It Is and How Can It Help

When data informs decision making, there exists an opportunity for business leaders to glean high-level, forward-looking insights about the operations and efficiencies within a company. But many businesses find their data housed within disparate departments and systems, making them unable to make key connections between data sets. How can business leaders distill meaning from the data flooding their organizations, sharpening information gleaned from across the company into informed strategy?

Many business leaders have pinpointed data warehouses as the answer. The data warehousing market in the United States was valued at 13 billion dollars in 2018 and is expected to grow to 30 billion dollars by 2025 – more than doubling in five years.

What is a Data Warehouse?

Data warehouses are powerful strategic tools organizations use to store and analyze large amounts of data, integrating multiple data sources into a single centralized system. A data warehouse is designed to improve the performance and speed of decision-making by making interconnections between different elements of a business more visible, enabling more integrated enterprise-wide thinking.

Data warehouses come in various forms, from cloud-based solutions to traditional on-premises and hybrid solutions. Whichever option you use, data warehouses can help your organization leverage its existing investments while providing insight into core operations and mission-critical information with increased efficiency. Here, we'll cover the benefits of data warehouses, their role in business intelligence and key considerations for implementing a data warehouse for your organization.

Benefits of Data Warehousing for CFOs

Without any single mechanism for identifying patterns and trends, business leaders will miss a key opportunity to gather a comprehensive, holistic picture of a company’s data.  Data warehouses allow CFOs and other decision-makers to make faster, data-backed decisions by seamlessly pulling data from Excel spreadsheets, enterprise resource planning (ERP) systems, customer relationship management (CRM) applications and other applications.

A central advantage to data warehouses is that they require data to be standardized. Creating standardized data ensures consistent and accurate interpretation, and is necessary for running effective data analytics and implementing artificial intelligence (AI) applications against the data. Additionally, when data is standardized, the opportunity to draw comparisons between and benchmark against peer companies and industry trends is unlocked. Management can then derive insights that allow for action-oriented decisions, such as identifying that a company is spending more on materials than regional competitors –spurring a reconsideration of suppliers and maximizing return on investment.

The Role Data Warehouses Play in Business Intelligence

Data warehouses play a crucial role in business intelligence. With the amount of data businesses generate daily, it’s becoming increasingly difficult to keep up with trends and uncover valuable insights. Data warehousing can help make sense of all the data by providing a single source of truth for all data on customer preferences, market trends, financial performance, operational efficiency and more. When this data is easier to understand and navigate, executives can identify trends, uncover new opportunities and gain competitive advantages.

The resulting bird’s eye view of a company’s operations would otherwise be impossible to access, and it eliminates the need to enter and organize data from multiple sources manually. For example, a data warehouse can bring together information about customer purchase histories, inventory levels, staffing and revenue growth into a single picture that provides a looking glass into a company’s future – allowing more proactive decision making and helping identify the symptoms and solutions for financial pain points.

Data warehouses also enable business leaders to extract data marts, specialized subsets of data centered around a specific business function, such as sales or marketing. Data marts can filter information from the data warehouse to isolate a business area or department, translating the larger body of information at hand into an area of focus to help center actionable strategy related to limited discussions or scenarios.

Key Considerations for CFOs When Implementing Data Warehouses

When implementing a data warehousing strategy, there are several key considerations to keep in mind.

Upfront and Ongoing Costs

While a data warehouse undoubtedly delivers many benefits, it also includes upfront and ongoing costs. Upfront costs can include the cost of hardware and software, installation, required training and consulting services needed to get the data warehouse established. These one-time costs can be substantial, but they are necessary investments that can yield returns in helping to identify efficiencies and ensure better strategy down the line.

Ongoing costs include upgrades, maintenance and support fees, storage, data transfer and, importantly, personnel costs for running the system. While identifying a data analyst – or a team of analysts – to manage system integrations may seem like an added expense, data warehousing will allow for information that was previously entered and maintained manually to be automated, unlocking the potential for freeing up talent to fuel the digital transformation.

Integration

Integration with other systems is also essential because data warehouses are only as powerful as the sources they pull from. By integrating with other systems, such as ERP and CRM systems, you can ensure that your data warehouse contains the most up-to-date data.

Determining how to get applications to talk to one another will require an application programming interface (API). API integrations allow companies to automate tasks by integrating their existing in-house software with third-party, cloud-hosted applications – often efficiently and at a low price. Using API, new application components can be integrated into a company’s existing architecture, meaning third-party technologies, tool and software are plugged in and ready to use with minimal effort. The investment in APIs has exploded in recent years, with over $2 billion invested in recent years.

Data Security

Security is another crucial consideration when implementing a data warehouse. Data warehouses can contain vast amounts of sensitive information, so it is vital to ensure that appropriate measures are in place to protect the data from unauthorized access.

Data Backup and Recovery

It is important to implement a comprehensive backup and recovery plan to protect your data warehousing investment and ensure uninterrupted access. Backup and recovery plans can help ensure that data is always available in the event of an unexpected interruption. Cloud-based backup solutions make recovering data quick and easy in an emergency.

By taking into account all of these considerations, you can ensure your data warehouse is secure, cost-effective, and able to generate insights that drive success. For more information, contact our experts today.