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Moving to the Cloud for Better Data Analytics and Business Insights


By Jeff Schodowski, Global Director of Analytics, Datavail

Businesses that are looking to take advantage of the benefits of moving their analytics platforms to the cloud, such as additional capabilities not available on-premises, as well as increased scalability and flexibility, may not have the necessary experience or expertise to traverse the intricacies a cloud migration entails – and also may not be able to fully realize the advantages they were initially hoping to achieve.

This article provides some best practices for companies to consider in order to achieve their goals, as well as overcome obstacles they may run up against during their cloud analytics migration journey.

  • Make Sure to Have a Strategy – This includes your tools and technologies, and complete foundation. Does it make sense to start your analytics cloud migration before upgrading and future-proofing, or should your first take a look at your infrastructure including your databases, as well as your security and data governance policies. Is your company also prepared for the shift from a Capex to an Opex or pay-per-use model.
  • Check Your Organization’s Data Quality – In order to be able to use the raw data that is coming from within your organization, such as multiple departments, and also from external sources such as vendors, you need to make sure that all data is consistent and reliable. This includes evaluating your data governance program, master data management (MDM), and data catalog. If the data quality is not trustworthy, the analysis conducted using it – regardless if robust cloud technology is being used – and the decisions that are made based on it will not be dependable.
  • Evaluate Your Complete Technology Stack – Make sure that each tool and technology in your platform has a definite purpose, and aligns with your business goals. Often, companies purchase and implement tools that are the most cutting edge or popular rather than what is most appropriate for their situation and needs, and the objectives they want to attain.
  • Create Goals for What You Want to Get Out of Your Cloud Analytics – Each company’s situation is unique, including the challenges they are trying to overcome. For example, one of our key customers, which is a large quick-service restaurant corporation, had large amounts of data coming in from thousands of locations across the globe. They needed to modernize their data operations to develop a better method of collecting, validating, and categorizing the varying quality of point-of-sale data from so many locations – and this included revamping the various tools and technologies they needed to implement in their cloud analytics infrastructure to reach their business goals.
  • Choose Which Cloud Platform is Best For Your Circumstance – A cloud provider such as Amazon Web Services (AWS) can provide the various services and tools needed to address a company’s cloud analytics needs, such as data ingestion and ETL (extract, transform, load), data storage and warehousing, and visualization and reporting. Complete a holistic evaluation of the cloud and best-in-breed technology providers and the tools and services they offer to ascertain how they work with each other in your cloud environment, and if they address the business problems you are trying to solve.

You cannot underestimate the importance of data quality and the ability to make timely decisions based on insights obtained from data analytics, as companies continue to attempt to acquire an edge over their competition.

This article was originally published in RT Insights