Download the slides here>> In the age of big data, even data assets generate (what else?) data. The secret? These metadata details offer powerful guidance that can help newcomers find, understand, and use those assets more powerfully and efficiently than their predecessors. Yet putting this into practice demands experience. Join Alation experts, to learn:
Solidatus Demo: Harnessing Active Metadata, Lineage and Data Blueprints for Better Data Governance
Download the slides here>> How does your data really flow around your organization? Do you have transparency on its context, and on the people and processes it touches and impacts? Underpinned by active metadata, Solidatus helps organizations create living, dynamic blueprints of their data. An understanding of data lineage is key before embarking on […]
Master Data Management Best Practices
Modern businesses can stay competitive by using the best practices for master data management (MDM). These best practices promote the use of clean, accurate data about suppliers, customers, and products. This, in turn, supports better analytics and business decisions. A master data management solution supports the development of master data, which can provide consistent, accurate data […]
Leveraging Data Pipelines to Meet the Needs of the Business: Why the Speed of Data Matters
Gone are the days when customers would place an order and patiently wait for hours or even days for goods to be delivered, or when letters would travel through snail mail to reach their recipients. Today, businesses and individuals expect instant access to information and swift delivery of services. The same expectation applies to data, […]
Logical Data Management for Environmental, Social, and Governance (ESG) Initiatives
Driven in large part by a growing awareness of the effects of unchecked carbon emissions, environmental, social, and governance (ESG) initiatives have been gaining momentum across companies in Europe and, more recently, the U.S. Some verticals, notably financial services, are beginning to tie ESG information directly to investment decisions, while all companies are realizing that […]
3 Reasons Manufacturers Must Get Data Governance Right in 2023
In the manufacturing space, digital transformation has made data the oil in many machines – and much like oil, it needs refinement and enrichment. This can be carried out via Data Governance. Good Data Governance translates to smarter, quicker, data-driven decisions, as well as more efficient resource management, reduced security risks, greater trust from customers […]
Unlock the Power of Data with Unified Data Controls
Artificial intelligence (AI) could boost company productivity by 1.5%, increasing S&P 500 profits by 30% over the next 10 years. The rapid success of generative AI technologies such as ChatGPT is an excellent example of how companies can shape their fortunes by harnessing the power of the data they hold. The insights from data enable businesses across […]
What Is Data Governance? Definition, Types, Uses
Data Governance (DG) is a business program and bedrock that supports harmonized data activities across the organization. It accomplishes this goal as a formalized framework implemented to the specifications of a corporate Data Strategy. Applying governance, as a whole, requires connecting different components – such as roles, processes, communications, metrics, and tools – to increase the likelihood that the […]
RWDG Webinar: Gaining Leadership Support for Data Governance
Download the slides here>> This webinar is sponsored by: About the Webinar A commonly used best practice associated with standing up Data Governance programs is that “senior leadership support, sponsor, and understand Data Governance” and the activities and resources associated with governing data. The question becomes, “How do we get leadership’s support when it […]
Testing and Monitoring Data Pipelines: Part Two
In part one of this article, we discussed how data testing can specifically test a data object (e.g., table, column, metadata) at one particular point in the data pipeline. While this technique is practical for in-database verifications – as tests are embedded directly in their data modeling efforts – it is tedious and time-consuming when end-to-end data […]