One of the most important decisions you will make about your data is which platform to store it in. This is, by a good measure, the technical decision with the most leverage in the program for years to come.

There are innumerable choices and buzzword-laden variations when it comes to legitimate data platforms. Each has its strengths and weaknesses.

MCG has helped dozens of organizations large and small select their storage platform. This includes the largest data warehouse in the world (twice!) through to start-up organizations on a shoestring budget.

William has been an IT decision maker, who implemented a multiple best-practice award-winning data warehouse. For 15 years of consulting, with his teams, he has been helping clients reap the same benefits.

William’s experience as a Version 1 developer of the industry leading database management system is an experience allowing him to get “under the hood” with all data platforms.

We have conducted these published benchmarks and more: SQL Server vs Google BigQuery, Snowflake, Amazon Redshift (2ce); Vertica in Eon Mode vs Google BigQuery; Enterprise APIs: Kong vs Apigee, withheld; Actian vs Snowflake, Amazon Redshift (2ce); Embedded IoT on IOS: Actian Zen vs SQLite; Data Lake: Microsoft Azure Data Lake Gen 2 vs Amazon EMR, Google Data Proc; SQL Server vs Google BigQuery, Snowflake, Amazon Redshift; Withheld vs Snowflake; Embedded IoT: Actian Zen vs SQLite; Azure SQL Data Warehouse vs. Amazon Redshift; Vertica in Eon Mode vs Snowflake; Actian vs Amazon Redshift, Microsoft SQL Server 2017, Snowflake, Cloudera Impala; Streaming: Apache Pulsar (Streamlio) vs Kafka; Vertica vs Amazon Redshift; Hadoop Integration: RedPoint vs Informatica; Hadoop Integration: Talend Open Studio vs Informatica. We’ve also led many other benchmarks for client situations.

We are leading consultants and analysts. We have unparalleled exposure, experience, access, resourcefulness and curiosity in data platforms. For example, we put data warehouses in Hadoop (in the cloud) to prove to ourselves the pros and cons of doing it this way.

Let us explore with you these questions and more:

• Should you go best-of-breed or stick with one megavendor’s solutions?
• Should we put our data in the cloud?
• What should be our reference architecture for a platform?
• Beyond the slideware, what are clients really usually doing with the solution?
• How much should we concern ourselves with future and unforeseen uses of the data?
• What workloads can go on this platform and which will need to go someplace else?
• What is an acceptable level of data redundancy in the environment?
• What should we expect for the people costs for our project?
• How does a platform fit with my existing toolset?
• What’s important that we’re not considering?

We help clients short-list with confidence, run Requests for Information, Requests for Proposals and Proofs-of-Concept. Packages come as per-hour consulting, fixed price for support through the decision and/or implementation, and retainer-based.