This is the third and final blog in this series, to read the previous blog click, here.

 

In the first post, I urged you to stop using star schema dimensional models because they were obsolete. In the second post, I elaborated on why star schema dimensional models were obsolete using Ralph Kimball’s own reasons for justification of the star schema dimensional model.

Move your Data Lake to the Cloud

The cloud is the best environment for a modern Data Lake. Cloud computing is the on-demand delivery of IT resources over the Internet with pay-as-you-go pricing. Instead of buying, owning, and maintaining physical data centers and servers, you can access technology services, such as computing power, storage, and databases, on an as-needed basis from a cloud provider.  Personally, I think the Google Cloud Platform is the best data management platform on the planet. Moving to the cloud for Data Lake Management will save costs over on-premises architectures.

 

Storage

Move your data lake to the cloud and move your storage with it. Cloud storage automatically expands as you need it. Cloud storage is inexpensive, fast, and reliable. Using cloud storage will help save labor costs and overhead costs for on-premises architectures.

 

Use a Modern Data Lake Engine

Modern Data Lake engines are in the cloud like BigQuery. They should be serverless and they should be able to search through billions of rows of data in seconds. They should be able to provide some measure of federation with other operational OLTP and noSQL data sources. They should be able to access data in other public clouds and they should integrate with data visualization tools and data science platforms. Modern cloud-based data lake platforms are the best performing data management platforms available.

Use Multiple Data Zones in the Data Lake

Data zones are typically implemented as directories or datasets. Ingest/land data in the same format as the source systems in what I like to call the discovery zone. Integrate data joining attributes from multiple tables into one wide table in the strategic zone and please any data that is mastered from across the corporation into the optimization zone. This process of zoning data and creating wide tables helps data users better understand the data and makes it easier to use to make better business decisions.

 

Move from Reporting to Business Intelligence

Use data visualization tools. Don’t drill down drill across. Don’t create reports, interactively looks for patterns and trends. Don’t print reports, share interactive data visualization URLs. I am talking about using tools like Tableau, Qlik, Power BI, Looker, or my favorite Google Data Studio.

 

The Modern Knowledge Worker

The primary skill for many modern knowledge workers is the ability to manage data in a spreadsheet. So, begin the long process of enhancing the skill of the knowledge works in your organization. Teach them SQL and teach them to use data visualization tools.  It may also be beneficial to enable them to use some citizen data science tools.

Perficient’s Cloud Data Expertise

Our cloud, data, and analytics team can assist with your entire data and analytics lifecycle, from data strategy to implementation. We will help you make sense of your data and show you how to use it to solve complex business problems. We’ll assess your current data and analytics issues and develop a strategy to guide you to your long-term goals.