Thinking of moving to a Cloud Data Warehouse? 

Today’s enterprises rely on the effective collection, storage, and integration of data from disparate sources for analysis and insights. These data analytics activities have moved to the heart of revenue generation, cost containment, and profit optimization. As such, it’s no surprise that the amounts of data generated and analyzed, as well as the number and types of data sources, have exploded. 

Data-driven companies require robust solutions for managing and analyzing large quantities of data across their organizations. These systems must be scalable, reliable, and secure enough for regulated industries, as well as flexible enough to support a wide variety of data types and use cases. The requirements go way beyond the capabilities of any traditional database. That’s where the data warehouse comes in. 

Do you need a data warehouse? 

Some businesses and industries require data analysis that is not only massive in scale, but also ongoing and in real time. For example, some service providers use real-time data to dynamically adjust prices throughout the day. Insurance companies track policies, sales, claims, payroll, and more. They also use machine learning to predict fraud. Gaming companies must track and react to user behavior in real time to enhance the player’s experience. Data warehouses make all these activities possible. 

If your organization has or does any of the following, you’re probably a good candidate for a data warehouse: 

What is a data warehouse used for?  

Cloud data warehousing offers a range of solutions that can benefit an organization. Here are some common uses: 

Consolidate siloed data 

Quickly pull data from multiple structured sources across your organization, such as point-of-sale systems, websites, and email lists, and bring it into one location so that you can perform analysis and get insights. 

Make decisions in real time 

Analyze data in real time to proactively address challenges, identify opportunities, gain efficiency, reduce costs, or proactively respond to business events. 

Enable custom reporting and ad hoc analysis 

Keep historical data on a separate server from operational data so that end users can access it and run their own queries and reports without impacting the performance of operational systems or needing to get help from IT. 

Incorporate machine learning and AI 

Collect historical and real-time data to develop algorithms that can provide predictive insights, such as anticipating traffic spikes or suggesting relevant products to a customer browsing a website. 

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Learn more about how Innovoco facilitates Cloud Data Warehouse projects by starting small and simple.  

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