![]() ![]() Self‑service and on‑demand tools and frameworks further empower data engineers and data scientists, while interactive query coupled with better data availability facilitates more informed decision‑making. With the Data Lakehouse running on‑premises or in a colocation facility, better data quality and control for BI and reporting give you the power to run critical analytics projects with more confidence in the value of the results. This Data Lakehouse enables self‑service access to reliable, quality data for all users so they can run analytics, AI, ML and other data‑driven workloads to create value from data. ![]() Consisting of PowerEdge servers, PowerScale and ECS Object Storage, PowerSwitch networking and powered by Apache® Spark® and Kafka® with Delta Lake technologies and Robin Cloud Native Platform, this solution is designed to help you harness more data to transform insights across your organization. It provides rapid, direct access to trusted data for data scientists, business analysts and others who need data to drive business value. The new Dell Validated Design for Analytics – Data Lakehouse supports business intelligence (BI), analytics, real‑time data applications, data science and ML in one platform. To compete in the digital era, your organization needs new solutions that evolve data management from siloed, rigid, costly and slow to unified systems that enable analytics and AI with speed, scalability and confidence. However, this adds to the complexity and cost of the analytics landscape. Today, many organizations use a data lake in tandem with a data warehouse - storing data in the lake and then copying it to the warehouse to make it more accessible. However, data warehouses aren’t set up to handle the increasing variety of data - text, images, video, Internet of Things (IoT) - nor can they support artificial intelligence (AI) and Machine Learning (ML) algorithms that require direct access to data.Īdding a data lake promised to help solve these issues, by enabling enterprises to capture all types of data - structured, unstructured and semi‑structured - more flexibly and cost‑effectively than traditional data warehouses. Traditional data management systems, like data warehouses, have been used for decades to store structured data and make it available for analytics. But the distributed nature of data can make that complex and costly - setting up barriers to insight and innovation. In the data‑driven era, you must be able to generate value from all your data capital, from the intelligent edge to core data centers to multiple clouds. Energy, Climate Action & Sustainability.
0 Comments
Leave a Reply. |