Last week New Signature participated in a panel discussion at Microsoft’s Ft. Lauderdale SQL 2016 Roadshow. The topics presented included ways to modernize an organization’s data platform and how to think about big data as it pertains to an organization’s current data architecture. Presenters introduced the new SQL 2016 features, including real time operational analytics, in-memory operations for mission critical performance, faster insights, and data platform optimization. Given these enhanced capabilities, how can organizations start thinking about data platform modernization? One way to start is to assess how an organization currently interacts with data and determine where they fit on Gartner’s Analytics Maturity Model (Figure 1).

Gartner's Analytics Maturity Model

Figure 1: Gartner’s Analytics Maturity Model

Typically, an organization’s data usually lives in big silos and comes from different sources, ranging from legacy custom applications to third party CRM, ERP, HR & Finance applications. The data is disconnected and data management is complex, time consuming, and mostly manual. Most organizations currently still fall in the Traditional BI space, meaning that data is shared as static reports. It represents a historical perspective.

This historical view helps address “What happened?”, and the supporting visualization tools help answer “Why did it happen?”. The creation of the visualizations is typically a manual process with steps that transform data from its original state to a graph or a dashboard. The reason Traditional BI is considered reactive is because it looks at the past for insights on patterns that have already occurred.

A modern data platform enables organizations to not only to intelligently consolidate data, improve operational efficiencies, enhance their data store and security, but also provides the necessary features to expand their analytics capabilities. These capabilities ingest historical data into an intelligent architecture to predict “What Will Happen?”. The highest level of analytics maturity is building recommendations engines that incorporate machine learning algorithms to answer “How can we make it happen?”. This is called predictive analytics. Predictive analytics transitions the Traditional BI organization into a proactive management of data. A modern data platform enables organizations to make this transition easier and cheaper than in the past.

Joseph Sirosh, Corporate VP for Microsoft’s Data Group, said “Data is the New Electricity” during his presentation at the Data Driven event which focused on SQL 2016. In order to harness the power of data, organizations require technologies that are flexible, secure, easily scalable, easy to integrate, and built to support different types of user – from DBAs to Data Scientist. SQL 2016 provides the modern architecture for organizations to expand their data management and analytics capabilities and help cultivate a data-driven culture by democratizing data. As people across the organization start to see the value of analytics, they will further embrace advanced analytics and increase return on investment.

SQL 2016’s advanced analytics value proposition is to accelerate the speed of business. The in-database Revolution R platform truly makes SQL 2016 a comprehensive analytics data platform. One of the most impressive features is the parallelized processes built in the R service that efficiently distributes workloads within memory and reduces the resources to run big data analytics. Also, users can write scripts once and deploy anywhere, including the ability to deploy to Hadoop without having to recode. The integrated R platform allows Data Scientists to interact directly with data to create models and experiments, while also allowing DBAs to manage data and analytics together.

SQL 2016’s new features include the following:

  • In-memory enhancements: operational analytics and enhanced performance
  • Highest performing data warehouse: petabyte scale data warehouse
  • Enhanced security: always encrypted for protecting data at rest and in motion
  • Advanced Analytics: in-database analytics at massive scale with Revolution R
  • Mobile BI: end-to-end mobile on any device with self-service BI capabilities
  • Stretch Database: decreased storage costs by sending policy-based data to Azure

With these impressive new features, Microsoft is providing customers with the intelligent architecture to mature into an advanced analytics, harness the power of data by democratizing the experience to all types of users, while minimizing upfront investment and complexity to build scalable solutions that fully realize value from data. Organizations can mature from hindsight to insight, insight to foresight in a significantly shorter amount of time.