Data intelligence helps organizations create new customer experiences, accelerate operations and capitalize on new market opportunities. It also gives them the agility to pivot when the unexpected strikes.
While becoming data-driven makes great sense, some organizations struggle to put it into practice. Adopting a company-wide data culture can be particularly challenging, requiring companies to overhaul how they operate from the board room to the shop floor. On the technical side, IT teams must liberate and unify data long segregated in departmental silos so IT can provide broad accessibility and comprehensive analytics.
Some businesses have stumbled in their data transformation initiatives, causing them to question whether the effort is worth it. Recent research would suggest that it is worth it: IDC estimates that organizations that excel at leveraging data in decision-making enjoy more than three times greater revenue and nearly two-and-a-half-times greater profit than those who don’t.
Generally, organizations that succeed with data-driven initiatives have built and executed a cohesive data strategy. That strategy is reflected in how the business operates, which requires buy-in at executive levels and buy-in across departments and business units. The goal now is to have more data to base decisions on for greater accuracy, rather than relying solely on collective experience.
Executing the strategy necessitates aggregating data and expanding access company-wide for analytics to expose bigger-picture insights and trends. The combined data serves as a single source of truth for creating corporate value that runs the gamut from gauging customer sentiment to troubleshooting IT snafus to averting supply-chain delays.
The Role of the Data Lakehouse
A data lakehouse is one solution that organizations can use to help break down data silos and use as a foundation for an intelligent data ecosystem. It combines a data lake’s ability to store data in any format—structured, semi-structured, and unstructured—with the performance, security, and governance strengths of a traditional data warehouse.
The lakehouse provides central access to data as-is, independent of format. Organizations can run a variety of analytics on it to improve decision-making, from dashboards and visualizations, real-time analytics and machine learning. Open interfaces enable data scientists, business analysts and others to use their favorite analytics tools to access and analyze lakehouse data.
Building a Modern Data Ecosystem
While becoming more data-driven is a formidable undertaking, it’s becoming a competitive requirement in the digital economy. The same IDC report found that more than 84% of teams who excel at using data in decision-making get answers in minutes or hours compared to only 3% companies who don’t.
Culturally, companies need to commit to using data to drive decisions. At the IT level, they require unified data infrastructures, built around a data lakehouse, with the following characteristics:
- Affordable, scalable, and reliable storage
- Security and governance
- A holistic, integrated view of company-wide data
- Broad analytics capabilities, including the ability to process streaming data in real-time and machine learning
- Automation, including continuous learning and adaptability
- An online data catalog
With the Dell Validated Design for Analytics – Data Lakehouse, organizations can stop chasing data and start using it to create value for the organization instead.
Want to learn more about data lakehouses and how to succeed with your data-driven initiative? Read the Dell Validated Design for Analytics – Data Lakehouse Solution Brief.
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