Data Management

Showing 61 - 70 of 175 pages tagged with: Data Management

Value Adds of Modern Data Management and the Role of Big Data & Analytics

Podcast Guest: Mark Pritchard, Director of Sales Engineering (EMEA), Denodo

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Future proof Data Management Through Logical Architectures Data Fabric and Data Mesh

Presented at DATAVERSITY Demo Day – Enterprise Data Management ToolsData fabric and data mesh are two concepts frequently mentioned in conversations surrounding enterprise data management. Over the past two decades, enterprises have managed data by oscillating through cycles of centralization and decentralization. Despite the abundance of options, the conundrum remains — businesses want data to be in one place, and easy to find. Collecting all the data into a single location continues to be a challenge. Data fabric and data mesh designs, powered by data virtualization, can help businesses...

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Logical Data Management Approach for Smart Government

Public sector organizations face operational, regulatory, organizational, and cultural challenges as they attempt to become more agile, resilient, relevant, and reliable in the digital age. For the Singapore Government, becoming a Smart Nation — becoming digital-to-the-core — has meant defining a proven data strategy and innovative mandates to progress toward achieving this goal.Digitalization is a key pillar for such a transformation, accelerating the use of data and technology to become a fully data-driven organization.Read this Industry brief to learn how to leverage data in the optimal...

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The Evolution of Data Stack: From Query Accelerators to Data Fabrics (EMEA)

The data landscape has become more complex with new use cases like IoT, Streaming and Edge analytics. To better manage enterprise data distributed across data lakes, data warehouses, and many other systems residing on-premises and in the cloud, enterprises are turning to various data management technologies like query accelerators, data virtualization, and data fabrics. Each address specific needs of an organization, but which is the right solution to help you meet your business objectives?Join Denodo for a webinar featuring guest speaker, Forrester VP and Principal Analyst, Noel Yuhanna, to...

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The Evolution of Data Stack: From Query Accelerators to Data Fabrics (APAC)

The data landscape has become more complex with new use cases like IoT, Streaming and Edge analytics. To better manage enterprise data distributed across data lakes, data warehouses, and many other systems residing on-premises and in the cloud, enterprises are turning to various data management technologies like query accelerators, data virtualization, and data fabrics. Each address specific needs of an organization, but which is the right solution to help you meet your business objectives?Join Denodo for a webinar featuring guest speaker, Forrester VP and Principal Analyst, Noel Yuhanna, to...

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The Evolution of Data Stack: From Query Accelerators to Data Fabrics (NA)

The data landscape has become more complex with new use cases like IoT, Streaming and Edge analytics. To better manage enterprise data distributed across data lakes, data warehouses, and many other systems residing on-premises and in the cloud, enterprises are turning to various data management technologies like query accelerators, data virtualization, and data fabrics. Each address specific needs of an organization, but which is the right solution to help you meet your business objectives?Join Denodo for a webinar featuring guest speaker, Forrester VP and Principal Analyst, Noel Yuhanna, to...

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Myth Busters VIII: I'm moving to the Cloud, so I don't need data virtualization

So your company has decided to modernize its systems and migrate to the Cloud. Or, maybe, you're in the middle of this modernization and migration process right now. Taking advantage of the dynamic agility and flexibility of the Cloud offerings is certainly something to look forward to. But how do you ensure that your users can access the data that they need from the various Cloud and on-premise data sources - before, during, and after the migrations?The Cloud vendors will tell you that if you move your data to the Cloud, you won't need technologies like data virtualization. Is this true? Is...

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Logical Data Fabric and Data Mesh – Driving Business Outcomes

Presented at TDWI VIRTUAL SUMMIT - Modernizing Data ManagementWhile the technological advances of the past decade have addressed the scale of data processing and data storage, they have failed to address scale in other dimensions: proliferation of sources of data, diversity of data types and user persona, and speed of response to change. The essence of the data mesh and data fabric approaches is that it puts the customer first and focuses on outcomes instead of outputs.In this session, Saptarshi Sengupta, Senior Director of Product Marketing at Denodo, will address key considerations and...

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A Road Map to ESG Powered by Data Virtualization

IDC data shows that between 2021 and 2022 there has been a 10% increase in European organizations that are in the more mature stages of their sustainability initiatives; while for 19% of European organizations, over 10% of their IT budget is driven by sustainability-related actions.Data lies at the heart of an ESG framework, yet it remains a major hurdle. For most organizations data is stored in numerous different silos, from mainframes, to mid-range servers, different data warehouses, and of course the cloud. Enterprises have difficulty bringing all of this data together in a coherent way –...

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Reduce Supply Chain Friction through the Power of Integrated Data

Nobody needs to tell organizations dependent on supply chains that recent times have been full of uncertainty. Disruptions, economic challenges, global crises, and sudden changes in consumer demand continue to test resilience and agility. Supply chains today are complex and global, often involving hundreds, if not thousands, of suppliers and products at different stages of the journey from raw materials to finished goods in the hands of customers. However, data is distributed everywhere across global supply chains, and it is not always accessible, usable, up-to-date, or well governed....

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