Modern Data Warehouse Function 1: Data Processing

One thing a modern data warehouse does is data processing. Today’s data warehouses have the tools to analyse vast amounts of information so that they can be used in data analytics. 

For companies, this is a crucial capability. There’s more information being generated than ever before. If you can’t analyse it, you can’t gain value from it, and if you don’t evaluate information quickly, it loses its value. 

Modern Data Warehouse Function 2: Data Store for Analytics Programs 

The second thing a modern data warehouse does is serve as a data store for analytics programs. That means that analytics programs connect to the data warehouse and draw information from it for analysis.

Why is this important? This functionality allows you to connect other analytics tools to your data warehouse. You have the freedom to choose the solutions you want.

Siloed Data Warehouses vs. the Modern Data Warehouse

What’s the difference between siloed data warehouses and the modern data warehouse? It’s simple: siloed data warehouses don’t have the capabilities modern data warehouses do. 

A siloed data warehouse doesn’t connect to anything. It’s just an information repository that doesn’t have data processing functionality, nor does it connect to analytics programs. In contrast, a modern data warehouse allows you to get so much more out of your data thanks to data processing capabilities.

Use Cases for a Modern Data Warehouse

There are three use cases for a modern data warehouse:

• Integrate data
• Advanced analytics
• Real-time analytics 

Integrate Data

Take a second to think about the information that your organisation generates and consumes on a daily basis. You might create sales reports, and your marketing team is almost certainly looking at the results of its social media or email campaigns. While all of that information on its own is valuable, the value can sometimes increase dramatically when you combine data sources to gain new insights into your organisation.

One use case is integrating data into a modern data warehouse. This integration puts information in one place, so you can combine data sources for a different look into your operations. 

Advanced Analytics

No one has a crystal ball to predict the future. However, advanced analytics can give you a better sense of when something might happen. The modern data warehouse offers advanced analytics so you can make better business decisions. 

Many businesses want to know when they can expect customer churn. Advanced analytics would identify customers that are most likely to switch to a competitor based on attributes such as purchase history and interactions. This information helps companies determine whether it’s worth investing the resources to keep these customers, or whether they should focus on a more valuable segment. 

Real-Time Analytics 

Another use case for the modern data warehouse is real-time analytics. As the name implies, you can analyse information in real time, with no more waiting for information to load from systems of record. 

One way to use real-time analytics is for mobile device data. We use our mobile phones, smart watches, and tablets all the time. Device usage in and of itself can be valuable for organisations; with a modern data warehouse, you can connect to those data streams in real time to understand how users are interacting with your products and services. 

What Role Does Microsoft Azure Play in the Modern Data Warehouse?

Microsoft Azure provides the underpinnings that shape the modern data warehouse. It does so in three ways: 

• Providing the foundations for a modern data warehouse
• Offering advanced analytics  
• Delivering real-time analytics 

Providing the Foundations for a Modern Data Warehouse

Microsoft Azure helps you build a modern data warehouse with its suite of services. 

The Azure Data Factory ingests unstructured and structured data, which is then stored in Azure Data Lake Storage. Next, Azure Databricks (an Apache Spark-based analytics program optimised for Azure) prepares and trains the data so it can be modeled and served through Azure Synapse Analytics, Azure Analysis Services, and Power BI.

Offering Advanced Analytics 

In addition to providing the foundation of the modern data warehouse, Microsoft Azure also offers advanced analytics so you can make better business decisions. 

As mentioned in the previous section, Microsoft Azure has a number of services that ingest, store, prepare, train, model, and serve up data. The Azure Cosmos DB is a fully-managed database service that allows you to run globally distributed, low-latency operational analytics and AI on transactional data.

Delivering Real-Time Analytics

The third capability Microsoft Azure enables is real-time analytics. It uses Azure HDInsight to do so.

Azure HDInsight is an enterprise-grade service for open-source analytics. It quickly processes enormous amounts of data without the need to install hardware or manage infrastructure. You can also create optimised components for Apache, Hadoop, and Spark. 

How does it work? Azure HDInsight ingests unstructured data from sensors, IoT, clickstreams, and events. Then, it sends the information to Azure Data Lake Storage. From there, data is prepped, trained, modeled, and served up with other Azure products and services, including Azure Databricks, Azure Synapse Analytics, Azure Analysis Services, Power BI, and Azure Cosmos DB. 

Enlighten Designs: Helping You Build Your Modern Data Warehouse

Since 1998, Enlighten Designs has been helping customers gain value from their data. We’re proud Microsoft partners, having achieved Gold status in the Data Platform and Data Analytics categories. Recently, Enlighten was honoured by Microsoft for our data visualisation work with Sustainable Coastlines. To learn more about creating a modern data warehouse for your firm, contact us today.