How an Enterprise Data Warehouse Boosts Business Insights

Intro

Could you say that you’re using your data effectively? For most organizations, the answer is no. We’re at a point in time where we recognize the value and benefits of harnessing the power of the data we have access to – but on the implementation side, we know we’re falling short.

The enterprise data warehouse is changing this. Finally, businesses can access the actionable insights camouflaged in large amounts of data, leveraging these to get ahead of competitors and lead their industry for years to come. 

What is an Enterprise Data Warehouse?

An enterprise data warehouse, or EDW, is a repository in which all data is centrally stored. It’s set up so that data is ingested consistently, and it therefore contains huge volumes of structured data that can be effectively and efficiently queried. 

From a business perspective, it’s the infrastructure that enables various functions to add maximum value; providing a single source of truth and data-driven decision making capabilities to multiple stakeholders. 

Key Components of an Enterprise Data Warehouse

The major components of an enterprise data warehouse include:

• Data sources: These are all the points from which data flows into the system, like the CRM, sensors, databases, or other files. 
• ETL: “Extract, Transform, Load,” (or in “ELT” configuration) governs how data is pulled, cleaned, formatted, and fed into the EDW. 
• Storage: Typically data is organized in schemas, cubes, or tables.
• Data governance: Ensures the ongoing quality, security, and integrity of data
• Data access: Including SQL interfaces or business intelligence tools
• Performance: Can include optimization mechanisms for getting the most out of the enterprise data warehouse

Benefits of Implementing an Enterprise Data Warehouse

An enterprise data warehouse is so valuable to modern organizations because it supports better business decisions. It also offers advantages in terms of costs and performance. Here’s how:

Single source of truth

All data, from all systems, is centralized in one place. This means that there is a unified view, all stakeholders have access to the same information, and information from disparate sources can be combined to uncover insights and drive effective results. 

Quicker decision-making

Access to data is sped up tremendously, enabling decision makers to respond quickly to opportunities or threats. 

Advanced analytics

With an EDW in place, organizations can benefit from predictive modeling and trend identification. For example, in a manufacturing environment, an EDW can be used to identify production bottlenecks based on data around machine performance, downtime and throughput. The manufacturer can predict failures and schedule proactive maintenance – improving efficiency and driving real business outcomes. 

Enterprise Data Warehouse vs. Data Lake vs. Data Mart

It’s important to clarify the difference between an enterprise data warehouse, a data lake, and a data mart.

Enterprise Data Warehouse

This is a structured, centralized repository for all data in the enterprise that stores historical data. It’s optimized for queries and reporting, and is most valuable in terms of ensuring data consistency and better decision making across the enterprise. 

Data Lake

A data lake stores unstructured, raw data, or structured data in its native format. It’s flexible and is therefore mostly used in analytics, processing of huge amounts of data, and machine learning, often being used in a more experimental way. 

Data Mart

A data mart is actually a subcategory of a data warehouse, where the data mart is tailored to a specific function or department – for example sales or marketing. 

Best Practices for Enterprise Data Warehouse Implementation

When implementing an enterprise data warehouse, be aware of these best practices to get the most out of your solution:

Plan effectively: Define your objectives, and ensure your EDW supports your business requirements. Engage all relevant stakeholders to ensure buy-in and alignment, and to maximize the chances of adoption. Keep scalability in mind, as data volumes are only increasing. 

Focus on the data: What plans are you putting in place to ensure data quality? Make sure you establish the necessary processes and checks, including robust data governance policies. 

Choose your tools wisely: The platform you choose will have a significant impact on the outcomes you generate, and on the ongoing usage of the system. Choosing the wrong tool at the outset can have frustrating consequences. Therefore choose a solution that gives you the performance, affordability, and scalability that you need. 

Test and optimize: Thoroughly test, monitor, and optimize, especially when new data sources are being connected. 

FAQ

Q: How much does it cost to set up an enterprise data warehouse?

A: The actual cost of setting up an EDW can depend on numerous factors, such as the deployment type (on-prem, cloud, or hybrid), the volume of data, and so on. 

Q: What industries benefit most from enterprise data warehouses?

A: Any industry with large amounts of data that needs to regularly run complex queries will benefit from an EDW. These include healthcare, manufacturing, advertising, finance, retail, and telecom.

Q: How does an enterprise data warehouse support business intelligence?

Q: By providing a single source of truth, and combining all available data in one place in a structured way, business leaders can access unprecedented insights to drive better decisions. 

Meet SQream: Industry-leading GPU-Accelerated Data Processing

SQream is the difference between a good enterprise data warehouse and a great one. With its GPU acceleration technology, SQream enables organizations to extract deeper, more valuable insights faster – and at the fraction of the cost of other tools. 

No matter the amount of data, including terabytes or petabytes, SQream ensures that even the most complex queries can be run, unlocking the full potential of the EDW. 

Key benefits include:

• Scalability: Query massive amounts of data without compromising on performance
• Performance: Easily execute analytical queries on large datasets
• Faster insights: Access unprecedented time-to-insight thanks to the GPU-based solution
• Cost efficiency: Benefit from significantly lower overall TCO, compared to other tools
• Seamless integration: Connect with existing solutions via industry-standard connectors

With SQream, your organization can overcome the traditional data infrastructure limitations, unlocking the power of your data to provide unmatched insights, incredible value, and long-term industry leadership.

To learn more about how SQream can solve your business challenges, schedule a call here. 

Summary: Leverage Your EDW To Boost Business Insights

We looked at the ability of an EDW to cope with massive amounts of data and complex queries to provide business intelligence and vastly improved decision making capabilities. 

By following best practices, including leveraging SQream as part of your deployment, you can use your EDW to be the driver of your growth and success.