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Modernizing Data Analytics with SQL Server 2019

Introduction :

Businesses require near real-time insights from ever-larger sets of data. Large-scale data ingestion requires scale-out storage and processing in ways that allow fast response times. In addition to simply querying this data, organizations want full analysis and even predictive capabilities over their data.

Wide World Importers (WWI) is a traditional brick and mortar business with a long track record of success, generating profits through strong retail store sales of their unique offering of affordable products from around the world. Over the past few years, they have adopted an omni-channel strategy, meaning, different ways for consumers to purchase their products. These new platforms were added without integrating into the OLTP system data or Business Intelligence infrastructures. As a result, "silos" of data stores have developed.

Now, WWI is trying to cope with difficulties in combining these disparate data sources in varying formats into a single location where they can analyze the data in near real-time, joining related information where needed. They also want to be able to leverage AI to help their business grow and cut down maintenance costs. They would like to have all of these capabilities rolled into a single system, while minimizing code changes across their domain.

Objective :

Design a modernization plan for performing Big Data analytics, centered around scalable SQL Server 2019 capabilities, saving 25% taxes.
Data virtualization to unify complex joins of Sensor, Businesses data. Detect and fix PII and GDPR compliance by Masking, Security and Encryption.
Evaluate the customer scenario and requirements, giving best architecture that gains real-time business insights at scale, reducing downtime and cut in e-waste by 30%.
Performing machine learning, for a faster access to fresh data, Reducing maintenance costs and maximize logistics fleet availability on predicting battery lifespans & Sales forecasting.