Data and Analytics - eBook (EN)

Data, Analytics, and ML Playbook

Issue link: https://read.uberflip.com/i/1407728

Contents of this Issue

Navigation

Page 11 of 11

A STRATEGIC PLAYBOOK FOR DATA, ANALYTICS, AND MACHINE LEARNING Without an organizing framework, it's easy to be overwhelmed by the opportunities and challenges of building a modern, cloud-based data foundation. To help, AWS created the Data Flywheel, a holistic framework that applies the self-reinforcing loop principles set forth by Jim Collins to a data manage- ment strategy designed to maximize the value of data. The Data Flywheel outlines five fundamental steps to building a modern, cloud-based data foundation: � 1. Break free from legacy databases. Many organi- zations still have legacy, proprietary databases that are expensive, create lock-in, and carry punitive licensing terms. Moving to open-source databases can deliver cost efficiencies without causing a performance or availability hit. 2. Move to managed services in the cloud. As database platforms begin to scale up, IT time and administrative costs can grow as well. Cloud-based, managed database services reduce time spent on undifferentiated heavy lifting so teams can focus on higher-value activities. 3. Modernize your data warehouse. Traditional data warehouses don't have the ability to effectively store and analyze the growing volume and variety of data, which leads to data being stored in multiple silos. A modern "lake house" approach, including a data lake that can store unlimited volumes of data in various structured and unstructured formats, makes it much easier to catalog data, make it accessible, and ana- lyze it across the business. 4. Build modern apps with purpose-built databases. Move from antiquated monolithic apps that run on one-size-fits-all relational databases to highly distrib- uted microservice-based systems running on multiple purpose-built databases to solve each problem. This method frees the application from having to employ a single, overburdened database for every use case. 5. Turn data into insights. Data lakes, analytics, and machine learning help organizations gather smart, accurate insights faster and empower end users to see and visualize their data from any device or application. The five steps are not linear, which gives organizations flexibility depending on their current level of data profi- ciency. "You can start anywhere, and they build on each other," says Oberoi. IDG Communications, Inc. Summary Data, analytics, and machine learning have the potential to radically transform business processes and revenue models as well as shape future innovations. But data is only valuable if you can turn it into action. To become a true data-driven organi- zation, leadership teams need to shift culture to view data as a strategic asset. A modern, cloud-based infrastructure provides the scale, flexibility, and intelli- gence to support this shift and empower your business. For more information, click here 5 steps to building a modern data foundation 12 t 1 Break free from legacy databases 2 Move to managed services 3 Modernize your data warehouse 4 Build modern apps with purpose-built databases 5 Turn data into insights

Articles in this issue

Links on this page

view archives of Data and Analytics - eBook (EN) - Data, Analytics, and ML Playbook