Online Events

Due to time zones, events presented by American speakers will be spread over more days, and will take place in the afternoon from 2 pm to 6 pm Italian time

Data Teams: Managing Big Data Projects

ONLINE LIVE STREAMING

Apr 12 - Apr 13, 2021

By: Jesse Anderson

Mastering the Requirements Process

ONLINE LIVE STREAMING

Apr 14 - Apr 16, 2021

By: Suzanne Robertson

Agile Data Science 2.0

ONLINE LIVE STREAMING

Apr 19 - Apr 23, 2021

By: Russell Jurney

Data Visualisation

ONLINE LIVE STREAMING

Apr 26 - Apr 27, 2021

By: Andy Kirk

Practical Guidelines for Designing Modern Data Architectures

ONLINE LIVE STREAMING

Apr 28 - Apr 29, 2021

By: Rick van der Lans

Real-Time Big Data Systems with Spark Streaming and Kafka

ONLINE LIVE STREAMING

May 03 - May 06, 2021

By: Jesse Anderson

Designing, developing and deploying a Microservices Architecture

ONLINE LIVE STREAMING

May 07, 2021

By: Sander Hoogendoorn

Incorporating Big Data, Hadoop and NoSQL in Data Warehouse and Business Intelligence Systems

ONLINE LIVE STREAMING

May 10 - May 11, 2021

By: Rick van der Lans

Cloud Native Applications with Docker and Kubernetes

ONLINE LIVE STREAMING

May 12 - May 14, 2021

By: Sebastian Daschner

Free article of the month

April 2021

The Dilemma of Data Digestion

Most of us are familiar with claims made by vendors of business intelligence (BI) and analytics tools that some disappointingly low percentage—often 10% or less—of businesspeople are actually using data in their decision making. The solution proposed is, unsurprisingly, to be found in product X, and more generally in the adoption of self-service BI. The more experienced (read “older”) of us recall that BI vendors have been using the same argument and figures for some thirty years.

Why has the problem persisted? New analytic techniques and improved BI tools haven’t really helped. The problem, I believe, lies between the data and the people. Very few people can truly digest data and extract valid, nutritious information from it. Many examples exist, but use of data in the Coronavirus pandemic illustrates the problem well.

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