By embedding a range of SQL acceleration and data management tools, queries across a data lake based on object-storage systems are optimized and readily available in cloud computing environments. SME uses technology that sits directly on data lake storage, eliminating the need for data warehouses and copying the data, thus reducing storage and compute costs.
An open data architecture allows you to use best-of-breed tools directly on cloud data lake storage, eliminating vendor lock-in, and providing flexibility for adopting emerging technologies.
A data lakehouse provides direct access to your data lake. This approach leaves the data where it is, whether data lake or federated data sources, and allows you to query the data using high speed technologies and create representations of the process data. For example, a lot of our customers leverage a data lakehouse to speed up Power BI reports for more real-time insights.
A commonly cited disadvantage of data warehousing is the cost/benefit analysis. A data warehouse is a big IT project and requires a lot of time and budget to maintain and update as the business grows and adapts to the market.
We see organizations falter with deploying data lakes because managing petabytes of data at that scale was too challenging. For example, a data lake based on Hadoop can quickly become a data swamp as more data is added.
A data lakehouse is the combination of a data lake with an analytics engine. It provides direct access to a data lake using SQL for any use ranging from raw data access to analytics.
The unique ability of the lakehouse to manage data in an open environment, blend all varieties of data from all parts of the enterprise and combine the data science focus of the data lake with the end-user analytics of the data warehouse will unlock incredible value for organizations.
With a next-generation data lake engine, you can empower governed, self-service data access for data analysts and data scientists, with consistent semantics across all users, applications, and tools.
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An assessment of your Business Intelligence (BI) and reporting needs as compared to your current ability to fulfill those goals.
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Demystify these terms and look at similarities, differences, and what that means for the future of Business Intelligence (BI).
Finding the right Data Storage and Processing solution can result in better flexibility in scaling and workload management, better control of the cost of storage and computing, and a better source of your data that allows for real-time analysis and reporting. Learn how SME consults on finding the right strategies, objectives and activities to fulfill your strategic plan.Learn More
Data value is derived from it being real-time, automated, and easily integrated in minimal time. From heterogeneous sources that include production databases, data warehouses, SAP, and mainframe systems, to flat files and SaaS applications; we deliver to all major target platforms. Learn more about what our Data Integration and Automation solutions provide.Learn More
Without Data Governance and Literacy, the insights that are hidden in your data become limited. SME Solutions Group works to build data-driven cultures by implementing our Data Governance and Literacy solutions. We choose to work with partners that provide data glossaries, data catalogs, and other data management systems that help uncover the true insights in your data.Learn More