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:
- Multiple sources of disparate data
- Big-data analysis and visualization—both asynchronously and in real-time
- Machine learning/AI
- Streaming analytics
- Custom report generation/ad hoc analysis
- Data mining
- Data science
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.
Taken directly from: https://cloud.google.com/learn/what-is-a-data-warehouse
Learn more about how Innovoco facilitates Cloud Data Warehouse projects by starting small and simple.
Pick a day here, we’ll send you a Skip the Dishes/Uber Eats EGift Card, and we can chat over Teams.
Sneak preview:
- We will NOT bore you with the commonly cited benefits of cloud data warehouses
- We will present 2 specific paths to move from Legacy Data Warehouses to the Cloud:
- MS Azure – recent developments in Synapse and Databricks that make it very easy to build a data warehouse by starting off small and building up.
- Google BigQuery – Google has been trying to steal market share by offering rock bottom pricing and interesting features.
Pick a day here.