Organizations are increasingly likely to include data as part of their day-to-day strategy in order to derive business intelligence, but the value of that data is typically limited. Most organizations simply don’t have a good understanding of the underlying data they collect and store, and more time is spent searching for data rather than actually analyzing it...
Read how Nordea uses Waterline Data Catalog and Trifacta Data Wrangling for big data success. Swedish bank Nordea is a company with a particularly convoluted history. It was formed from the merger of four mid-sized banks, themselves building on a history of more than 300 companies. And to add to the complexity, these banks were located in the four Nordic countries, based around different legal backgrounds.
CRN® names Waterline Data to its 2017 Big Data 100 list. This annual list recognizes the ingenuity of tech suppliers bringing to market innovative offerings for harnessing the increasingly huge amounts of data generated in today’s digital world, raising the bar for data management and challenging established IT practices.
Working on the aspect of “connect the right people to the right data,” Waterline is dedicated to automating the discovery and intervening of data so that organizations can spend more time using data, and less time searching for it and better comply with data regulatory requirements thus reducing the costs associated with data redundancy and data hoarding.
Waterline Data has an impressive product catalog in the area of big data processing. (Article in Dutch)
Waterline selected to Constellation ShortList™ for Data Cataloging.
Comment améliorer la valeur commerciale des data lakes à l'heure où les entreprises rechignent justement à supprimer certaines données. Waterline Data propose de découvrir et cataloguer ces données invisibles afin d'alimenter la réflexion stratégique.
A group of California-based startup and early-stage data analytics and management companies (see Waterline in alphabetical order in this article) are bidding to make big data, including sensor data, more tractable for analysis.
Data cataloging is important for any organization that wants to make the most of its data, particularly as data sources and data-driven applications multiply and as data scale and diversity grows.