In today’s ever-changing and increasingly competitive market, organizations are challenged to find differentiation to set themselves apart and maintain momentum. The need to harness data for greater clarity and agility has never been more necessary as customer expectation heighten and our economy becomes more digitally driven. Simply gathering data, however, does not automatically deliver business value—it merely provides a pool of untapped knowledge. To make data valuable, it needs to be explored and interpreted to derive actionable insights.

Built on the Microsoft Azure platform, Azure Synapse is more than just a hub for gathering data—it is a powerful analytics service that incorporates Power BI, artificial intelligence (AI), and machine learning (ML) to surface insights that help you better understand both your business and your customers. With the right analytics solution, you can respond quickly to fluctuating industry demands, engage customers more effectively, and make data-driven decisions for a better future.

86% of business leaders say defining a data and analytics strategy is the top responsibility of their Chief Data Officers

What worked for your business in the past may no longer be enough to navigate today’s unprecedented changes. A new approach is required that prioritizes business intelligence and analytics to support greater agility and responsiveness. This means embracing emerging technology to democratize data and empower not just your C-suite—but your entire organization—with the right data and analytics tools to enable timely, insight-driven decisions.

Business intelligence: While typical analytics dashboards can offer some visibility into what’s going on in and around the business, self-service business intelligence tools like Power BI can provide more interactive visualizations and capabilities that end users throughout the organization can configure and leverage on their own to gain valuable insights.

Artificial intelligence: Adding an AI layer to your analytics can deepen your insights and identify unique trends or patterns that might be otherwise undetected by human capacity. It also speeds time to insight with faster, machine-aided analysis.

Machine learning: A subset of AI, machine learning can learn from data and improve over time to provide real-time predictive analysis and valuable business intelligence. Automated machine learning can assist both data scientists and business users by building advanced analytic models to aid in insight discovery.

A unified analytics experience

While democratizing analytics and insights is a necessity, a successful analytics strategy hinges on the quality and completeness of the data it’s built upon. In other words, it is essential to combine data across all disparate sources with a single platform in order to leverage a unified, holistic source of truth. Yet even with centralized data, it can be difficult to build and manage analytics models across the organization without a unifying service.

Azure Synapse and Power BI uniquely bring the capabilities of data unification and limitless analytics together, enriched with the power of AI and ML, all in a single management workspace with common security and governance. With a fully integrated analytics stack, all users—from business users to data scientists—can explore and engage with data while achieving faster time to insight and delivering greater impact. In fact, 85 percent of organizations leveraging Azure Analytics and Power BI report seeing measurable benefits from having well-integrated analytics databases and storage, data management stack, and BI tools.  By providing employees with the tools to harness your corporate data, you can help them make better decisions for your business.

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If you’d like to learn more about Azure Synapse Analytics and see a demo from our Data & Analytics Teams, please leave us a message below.