By  Ken Seier / 21 Jul 2020 / Topics: Artificial Intelligence (AI) Analytics

Now, more than ever, we need real-time clarity and insight to stay ahead of change and create a competitive edge for our business.
Data has the answers. It provides visibility, tools and intelligence to make smarter decisions and thrive in these volatile times. A data-driven culture can help you remain relevant to your customers, dominate the market, increase revenue and profits and invest for innovation and growth.
But without analytics data is just noise. With analytics however, data becomes insight.
In order to convert data into meaningful business intelligence, it has to be pulled out of silos, unified and democratized. It must be made usable, accessible and cost-effective. When you pair your data with an advanced analytics and business intelligence solution you transform it into a strategic competitive advantage.
Cloud-scale analytics is the new go-to strategy for turning massive datasets into actionable insights and tangible business value. A modern cloud analytics platform creates a centralized place for all your data — streaming, unstructured and structured — that ensures that the latest data (and all available data) is used for analysis in a consistent workflow.
It’s easy to build, deploy and scale with fewer resources, making it extremely cost-effective. It also supports better data governance and robust security controls. Most importantly, it empowers business users to do whatever analysis they want without involving the IT team. This accelerates the delivery of insights and powers agility and swift adaptability.
More insight: Download the IDG whitepaper to learn how the cloud and Artificial Intelligence (AI) are helping organizations improve their analytics capabilities at scale.
Microsoft® Azure® Synapse, an industry-leading end-to-end cloud analytics solution that unifies new streaming data with historical data to deliver rich analysis and actionable insights in near real time.
By bringing together SQL® data warehousing technologies, Spark for big data analytics and Azure Pipelines to orchestrate workflows in a no-code environment, Synapse offers a unified view of performance across an organization.
Thanks to our partnership with Microsoft, Insight’s Digital Innovation team has had the opportunity to build our experience and expertise leveraging Synapse to help clients build modern analytics systems that acelerate time to value.
Here are a few of key benefits of Azure Synapse:
Maximize the value of your data. Unifying, analyzing and managing all of your data — structured, unstructured and streaming — through a single plane of glass provides new insights and a more complete view of your business.
Power real-time discoveries. Support for Power BI® empowers data engineers to build rich data visualizations and business intelligence solutions that drive agility, responsiveness and competitive advantage with a mature data flow.
Enable simple self-service. By putting business intelligence directly in the hands of end users, Synapse reduces complexity and allows anyone to innovate faster and more effectively.
Support machine learning. Synapse also provides built-in integration with Azure ML to facilitate predictive modeling and advanced analytics with machine learning, making processes and applications more intelligent over time.
Build and scale with true agility. Perhaps most importantly, Synapse enables the development of end-to-end analytics solutions in days — not months — and the delivery of actionable insights in minutes.
As organizations across the world continue cope with market change, data will remain a key enabler for transformation. AI-driven analytics and business intelligence solutions like Azure Synapse play a critical role in providing the visibility needed to make smarter investments, take strategic risks and innovate for the future.
By focusing not only on how best to implement these technologies, but how to leverage and align new toolsets most effectively with end users, modern businesses can begin to achieve rapid and ongoing value from their data.