Imagine your organization is a ship navigating a sea of data. For years, you've relied on a traditional data warehouse as your sturdy vessel. But now, as the waters become more turbulent with increasing data volumes and complexity, the ship starts to creak under the pressure.   

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The sheer rise in the volume of data has led to industries struggling to navigate the rising complexities. Data-driven decision making has proven itself with its benefits. However, organizations are challenged to navigate the complexity types and drive meaningful insights. Grappling with issues inadequate infrastructure, the organization needs support ASAP. 

To put in scope, a mid-sized manufacturing company could have data across ERP systems in factories across cities, procurement data from suppliers, quotation data for its salesmen, sales data, marketing data from its diverse online & offline channels and customer behavior and demographics. The relevant data, keyword here being relevant, is extracted and requires context and a deep understanding before serious analysis can be done. To manage scale and complexity, the average business analyst is overwhelmed!  

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Reducing Data Debt by Using Data Lakehouse from Databricks 

Organizations now realize more than ever collecting copius amounts of data is ineffectual. Data is now needed to find paths that can directly affect top-line and bottom-line. Organizations can chop years of data debt and drive effective data strategies using a Lakehouse like Databricks. A data Lakehouse brings down complexity while accounting for scale and data complexity. Lakehouses support: 

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Unified data platforms: integrates across varied sources offering a consolidated environment. Advanced data analytics, data engineering and data science creates a unified view which provide strategic advantage to businesses.  

Reduced data movement: allows all operations to occur within a single environment, reducing the costs associated with data transfer and duplication. 

Lowering Maintenance Costs: The simplified architecture and cloud-native nature of data lakehouses reduce the burden on IT teams for maintaining and upgrading separate systems. 

Scalability & Flexibility: Cloud-as-a-Service(CaaS) model of Databricks allows organizations to scale storage and data processing functionality, avoiding the high costs of over provisioning.  

Adopting a Databricks Lakehouse is more than just a technological upgrade; it's a transformative step toward unlocking the full potential of data. By addressing common data warehouse pain areas, it empowers organizations to drive innovation, enhance efficiency, and achieve cost savings.  

With Exponentia.Ai, you can confidently navigate the complexities of cloud migration and harness the full potential of your data, driving innovation and accelerating your business transformation. Using industry best practices, cutting edge tools to identify and assess current infrastructure, identify optimal migration strategies, and execute the transition efficiently. It’s comprehensive approach includes meticulous planning, risk management, and thorough testing to ensure data integrity and security throughout the migration process. Additionally, ongoing support and optimization services maximizes the benefits of the new cloud environment, helping you achieve enhanced scalability, flexibility, and cost-efficiency.  

Talk to a Data Migration expert to learn more about how your organization can leverage Databricks to its full potential and see how it can help improve your organizational performance.   

Viresh Manjrekar

Pre-Sales

viresh.manjarekar@exponentia.ai