Human resources (HR) analytics helps you get insights into every aspect of your organization’s resourcing from hire and onboarding right through to leave and termination by combining data from many data sources. It helps you get insights into, and make predictions about, who and how many people you need to hire, how they need to be trained, how employees are performing, vacation/leave statistics, and what you can do to keep good employees around.
I am very excited to introduce Talend Data Streams, a brand new, cloud-native application that enables you to get streaming data integrations up and running in minutes all while providing unparalleled portability powered by Apache Beam.
BigQuery is a managed analytics service that provides advanced cloud data warehouse capabilities with a diverse set of features. One of BigQuery’s most significant differentiators is its distributed analytics engine, which transforms your SQL queries into complex execution plans, dispatching them onto our execution nodes to promptly provide insights into your data.
With the growing adoption of cloud-based IT infrastructures, the proliferation of mobile and IoT devices, and the rise of social media, companies of all sizes, across all industries are amassing huge quantities of data in differing variety, velocity, veracity and validity.
Growing your business will be your priority, especially in the early days, and you want it to do the very best it can.
In the past few years, there has been a shift in the data industry, leading to the emergence of a new category of data citizens: the ‘ad hoc’ or ‘citizen’ integrators. With these new personas adding to the (already long) list of data workers having access to corporate information, companies are needing to re-think the way they approach their data security and data governance strategies.
Qlik introduces management team, licensing changes, and new hybrid/multi-cloud, augmented intelligence and development features. Here's my take from Qonnections 2018.
The appearance of Hadoop and its related ecosystem was like a Cambrian explosion of open source tools and frameworks to process big amounts of data. But companies who invested early in big data found some challenges. For example, they needed engineers with expert knowledge not only on distributed systems and data processing but also on Java and the related JVM-based languages and tools.
5 ways to become a better data custodian under GDPR
How to best leverage your company’s most powerful asset
