Python

Advanced data science techniques, like machine learning, have proven to be extremely useful to derive valuable insights from your data. Even with a wide array of tools and technologies at their disposal, data scientists are still spending most of the time massaging and manipulating the data into a usable data asset.Data virtualization offers a new alternative to address these issues in a more efficient and agile way. Watch on-demand this session to learn how companies can use data virtualization to:Create a logical architecture to make all enterprise data available for advanced analytics...

Data Scientists spend most of their time looking for the right data and massaging it into a usable format. How can the Denodo platform enable the data scientist and data engineer?Join us as we explore and demonstrate how the Denodo 8.0 Data Catalog can help the data scientist and data engineers to find the relevant datasets quickly by using any metadata information and also using the respective categories and tags. Explore how the data catalog provides more information on the dataset allowing to define the descriptions for the views and fields, showing the associations with other datasets and...

Prologis, Inc. is a real estate investment trust headquartered in San Francisco, California that invests in logistics facilities, with a focus on the consumption side of the global supply chain. In this video Luke Slotwinski, VP Data and analytics with Prologis discusses in detail the data virtualization use case.This customer case study video will cover: ­ Prologis's business challenge ­How they used data virtualization to address this business challenge ­What the benefits of data virtualization are in their particular case ­Why they chose the Denodo platform ­How they plan to utilize the...

Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spent most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.Attend this webinar and learn:

Denodo customer presentation by Avinash Deshpande, Chief Software Architect at Logitech.

Harold works as product owner in the data management realm at Statistics Netherlands (CBS). He likes to think that his past as both IT developer and statistical researcher helps him in guiding useful product innovations at CBS. Before joining CBS almost twenty years ago, Harold studied political science and spent a couple of years working at a publishing agency.Visit Denodo DataFest 2019 to watch all the sessions on-demand.

Denodo customer presentation by Ryan Thompson, Director, Data Virtualization and Architecture at Prologis.

Avinash Deshpande, Principal, Big Data and Advanced Analytics at Logitech presents their data virtualization use case to successfully migrate to the cloud.

For several years, Logitech had been developing and delivering data services for analytics using on-premises systems. But provisioning data services for business users has been reactive, time consuming, and inefficient. The company’s modern product and service offerings, such as security video analysis and smart home devices, required predictive analytics, real-time data analytics, and cognitive science. To gain these capabilities, and be able to offer the right service to business users at the right time, Logitech wanted to move IT operations to the cloud. Cloud technology would empower IT...