Modern Data Analytics in the Cloud: Achieving an End-to-End Strategy

Join data management guru Dave Wells for this educational webinar on the data catalogs role, and how to get the best fit for your enterprise.Managing data in the age of big data and self-service analytics is a complex job. Managing data without a data catalog is difficult and fraught with risk. Data cataloging is the new gold standard for metadata and an essential component of modern data management. Data catalogs support data curation and data stewardship with intelligent and automated tagging, profiling, and linking to business glossary. They help business analysts and data scientists to quickly find data and evaluate the fit for their specific use cases. Strategically, cataloging is at the core of data asset management with direct impact for data governance, regulatory compliance, and analytic quality and efficiency.

75% of organisations believe they are not living up to their analytics potential. Research has shown that there are 5 major factors holding organisations back from fully utilising analytics in their business, these include: It’s time to change your experience with data and analytics. Data is growing exponentially and and more organisations are starting to realise that becoming data-driven is imperative to their success. Join us for this webinar as we take you through how to transform your analytics capability through data and AI to become a truly data-driven business.

A Data Strategy is a plan for moving an organization towards a more data-driven culture. A Data Strategy is often viewed as a technical exercise. A modern and comprehensive Data Strategy addresses more than just the data; it is a roadmap that defines people, process, and technology. The people aspect includes governance, the execution and enforcement of authority, and formalization of accountability over the management of the data.

Qlik offers solutions for creating analytics-ready data sets on the Databricks’ Unified Analytics Platform. They are designed to automate streaming data pipelines to make data seamlessly available to accelerate machine learning (ML), artificial intelligence (AI) and data science initiatives.