Modern Data & AI Solutions with Microsoft Fabric and Databricks

by Chris Bennett 5 minute read

AI is everywhere, and data is the currency of AI. That is no longer in question. What continues to keep many business leaders up at night, though, is how they can more efficiently, cost-effectively, and securely manage and leverage their data. Not only to garner better insights and help make better business decisions, but to accelerate digital transformation initiatives that make their organizations more agile and adaptive.

However, many companies have an outdated data infrastructure and massive amounts of data from many different sources. To fully explore the full potential of their data, they need to modernize their environment and adopt robust tools to manage and analyze their data effectively. And without a solid plan, AI is just a dream. At Hitachi Solutions, we understand this and work with customers every day to lay the groundwork for a modern data foundation. Our team of experts assess, advise, roadmap, implement, and support a new data estate based on a company’s goals and needs. We also use  the latest data management, analytics, and business intelligence tools and solutions — including our Empower Data Platform, cloud capabilities of Microsoft Azure, the data management capabilities of Microsoft Fabric, and the robust architecture of Databricks to ensure a seamless transition that is swift, secure, and scalable.

The Power of Microsoft Fabric and Databricks Integration

Why Fabric and Databricks? They’ve proven to be a powerful combination in handling complex data workflows for our customers. Fabric, with its robust data integration and orchestration capabilities, seamlessly connects disparate data sources, ensuring that the data pipeline is reliable and scalable. Databricks, on the other hand, brings in advanced data processing and machine learning capabilities, enabling us to extract valuable insights from the data.

By integrating these platforms, we have been able to offer our customers a comprehensive solution that covers the entire data lifecycle, from ingestion to visualization. This integration has significantly reduced the time and effort required to prepare and analyze data, allowing our customers to focus on gaining actionable insights that give them the competitive advantage to move their business forward.

Empower Adds Even More Value

Significantly enhancing the value of Fabric and Databricks is the addition of Hitachi Solutions Empower Data Platform. Leveraging Empower simplifies the complexities of a robust data strategy and streamlines the deployment and management of your Azure infrastructure. This accelerates your Fabric Lakehouse adoption, as well as orchestrates data movement across your organization and unlocks even more powerful analytical insights.

As an Analytics as a Service (AaaS) offering, Empower enables quick data flow into Azure Data Lake (gen2) with automated data onboarding, quality tools, APIs, and advanced monitoring. Utilizing Databricks’ strengths in data science and machine learning, Empower facilitates richer, faster, and more cost-effective insights, unifying modern data stacks and eliminating data silos to streamline data engineering, analytics, BI, data science, and machine learning processes.

Real-world Applications

The impact of integrating Microsoft Fabric and Databricks into customer data projects has been profound. The enhanced data management and workflow capabilities have been instrumental in driving innovation, efficiency, and better decision-making for companies in many different industries. Here are highlights from Fabric and Databricks in action:

  • One of our notable projects involved a major retail customer struggling with fragmented data sources and inconsistent reporting. By implementing Fabric and Databricks, we unified their data infrastructure, streamlined data processing, and created a centralized data repository. This not only improved data accuracy and accessibility but also empowered their analytics team to generate real-time insights, leading to more informed decision-making and increased operational efficiency.
  • In another instance, we assisted a healthcare provider in leveraging predictive analytics to enhance patient care. Using Databricks’ machine learning capabilities, we developed predictive models that identified patients at risk of readmission. The integration with Fabric ensured that the data required for these models was continuously updated and readily available. As a result, the healthcare provider was able to proactively address potential issues, improving patient outcomes and reducing costs.

Best Practices for Implementation

Having years of hands-on experience helping customers modernize their data estates, our data and analytics team has developed a solid set of standards for consistently and successfully implementing data strategies. These best practices include:

  • Understand the Data Landscape — Before starting an integration of Fabric and Databricks, it is crucial to thoroughly understand the existing data landscape. This includes identifying key data sources, understanding data flow, and recognizing any potential bottlenecks.
  • Collaborative Approach — Foster collaboration between data engineers, data scientists, and business stakeholders. This ensures the solution addresses technical and business requirements, leading to more impactful outcomes.
  • Scalability and Flexibility — Design the data architecture with scalability and flexibility in mind. This allows the solution to grow with the business and adapt to changing needs without significant rework.
  • Continuous Monitoring and Optimization — Regularly monitor the data pipelines and analytics processes to identify areas for improvement. Implementing a feedback loop helps in continuously optimizing performance and ensuring data quality.

Ready to Learn More?

As you can see, the combination of Microsoft Fabric, Databricks, and Hitachi Solutions Empower  is a true game-changer for companies looking to transform the way they manage and use their data — for AI, ML, automation, analytics, and more. So if you’re looking to embark on a data modernization and AI journey and want to learn more, you’ve come to the right place. We have a host of valuable resources that will help guide, advise, and support your initiatives:

Be sure and check out these assets, then reach out to our team of experts. We’d love to answer your questions and talk about your data and AI needs.

The Who & What Behind the Blog

Chris Bennett has spent the past 8 years in the consulting world working with Healthcare and Life Sciences organizations of various sizes to be able to innovate with Azure technologies. Backed by 20 years in the technology field he has worked in multiple technical domains giving him experience designing, implementing, and managing complex technical solutions. He also has a background in big data, custom app dev and high-performance computing and combining the three to bring cloud solutions to Bioinformatics and Genomics. Chris has leveraged his knowledge of Info/Infrasec and the modern lakehouse and data interoperability to start laying the foundation for Generative AI in secure environments capable of meeting organizational and regulatory security standards.