Adopting Cloud Analytics Just Became More Compelling
Capax Global Makes it Easy to Modernize Your Data Warehouse
By: Jerry Hawk, President at Capax Global
Featuring: Jesse Sullivan, VP Data + Analytics at Capax Global and Beth Barnes, Solution Delivery Lead at Hitachi Solutions
The Need for Speed
Having data available from all relevant sources is the critical component for any organization that is undergoing a rapid digital transformation. Just a couple of years ago it wasn’t unusual to significantly limit the amount of data going into a Dimensional Model — for analytics — to just the facts and dimensions required for operational reporting. Those days are long gone, with customers today needing as much data as possible to make critical business decisions. Of course, these new, wider workloads require incredible scale in a way that enables nearly unlimited capacity for future growth.
Microsoft has met this challenge with the Azure Data and AI ecosystem — from the original landing zone for data to the final self-service of high-value analytics with every enabling component in between. The ecosystem creates a simplicity that enables all consumers, from data scientists to the CFO, to perform analytics on their own.
At the heart of this solution is Azure Data Warehouse, a Cloud-Scale, high-performance MPP data warehouse that ensures that regardless of data size, processing plant requirements, or use-case, wide data sets across all sources can be served up to users, other services, or transformed at scale. Since Capax leads with ELT-first, meaning that we push untransformed data to Azure Data Warehouse and use the service as a processing plant, we gain the advantage of dynamic scale at the Load, Transform, and Distribution of data and often significantly reduce the licensing costs of typical “ETL” tools that are almost always implemented in an overly complex way.
A Quick Q+A with Our Data Warehouse Experts
Q: Why do you like working with Azure DW?
A: Jesse: I’m a huge fan of Azure SQL DW. Trying to think through why and it comes down to three key areas:
- First and foremost, performance and scalability are fantastic.
- As a developer, the time it takes to learn and become proficient in SQL DW is greatly reduced through common tooling including SQL Server Management Studio, SQL syntax, and TSQL syntax.
- Finally, availability. The ability to spin up an environment in minutes combined with pricing options to right-size your solution make this an MPP (Massively Parallel Processing) database now available to small to mid-sized businesses previously priced out of this type of technology.
A: Beth: SQL DW provides a tremendous amount of scalability and flexibility for our clients. We can quickly scale up resources as the needs of the client increase over time. Also, the global deployment and security features enable enterprise client to know their compliance requirements can be met.
Q: How can SQL DW accelerate enterprise reporting?
A: Jesse: The ability to stand up a big data environment in days/weeks instead of months and with tools and syntax most of your people already know, changes the discussion completely.
Q: How have you been using SQL DW with clients?
A: Beth: We have been using SQL DW to process large volumes of data in minutes to meet some of the near real-time requirements that the modern data warehouse needs. Many clients are moving to the cloud and have a requirement to modernize their environment. They are running away from many of the more costly, legacy data warehouse solutions. SQL DW provides an excellent option for them.
A: Jesse: The majority of engagements are around creating a Modern Data Platform enabling insight across the company — really all about centralizing all your information and enabling vastly improved analytics and insight across systems previously disconnected due to cost, scale, or capability constraints. Typically we are implementing an ELT pattern loading large volumes of data from many sources into Azure Data Lake and through to the Azure Data Warehouse and then further enabling the client with some combination of Power BI, AAS, Databricks, and more.
Q: What trends do you see with SQL DW and Data Science?
A: Jesse: Enablement. Enabling companies that wouldn’t have had the funding for on-prem big data solutions to leverage the PaaS (platform as a service) SQL DW solution for large scale data needs. Enabling analysts and consumers to directly interact with millions and billions of rows of data through Power BI and perform to expectations.
Summary
We have been marveling at how Microsoft has been able to keep the best parts of their history (creating easy to use software that is for the masses), while also making strategic improvements in areas previously not typically associated with Microsoft database platforms. With the recent announcement of GigaOm benchmarks, Microsoft Azure SQL Data Warehouse (ADW) now breaks new ground in price-performance — where they were already a leader. In addition, Capax Global continues to make it easier for enterprises to modernize their DW environments, benefiting from accelerators and a large team of over 100 people dedicated to Azure Data Services with significant production deployment experience.
Are you ready to jumpstart your Azure journey — LEARN MORE HERE.
