5 courses to improve your data literacy

What can you do to become data literate?

Big Data

What is data literacy and why is it important

Everybody that works with data, and that makes decision based on data, needs to have an understanding of the underlying, fundamental data management competencies – such as data governance, data quality and data modelling – that allow them to assess whether data is fit for purpose.

Big Data / Data Integration

Streaming analytics is key to leveraging value from M2M and IoT data

The constant and relentless nature of ‘always-on’ data generation also makes real time analytics even more important. Much of this data is only relevant now, in the moment, and once it is historical it no longer has worth. It must be analysed immediately and then deleted, otherwise no value can be gained.

Data Governance / Data Integration

Self-service BI and analytics are key to getting the insight you need, when you need it

Emerging digital channels are driving an explosion of useful data: data available in every area, from sensors to social media, our customers to our machines. Yet, without the ability to analyse this information, it is of no value, as we cannot use it to derive actionable insight that will allow us to deliver what our…

Big Data / Data Governance

AI is attracting regulatory attention

New questions on ethical implications, data privacy, or public safety are studied seemingly daily.

A matter of chickens and unicorns

How businesses manage the knowledge gap between decision makers and data specialists could be the difference between boom and bust

Three tips for laying the ground work for machine learning

data quality, hyperscale and Python – the foundation of machine learning

5 essential characteristics for a great data analyst

A few week’s back I wrote about the data translator – a role on the data science team that bridges the gap between the data scientist and the business. That got me thinking – what are the characteristics (that may be less obvious) that make for a good data analyst? 1. Intellectual curiosity and focus…

Why is data being taken more seriously?

I some times joke to my customers and prospects that I have been doing data since long before it was fashionable. One of the challenges of working in a relatively small market is that one tends to revolve through the same doors – having got a “not now” response i tend to come back six…

Are you struggling to really track lineage?

Date lineage is increasing important to business users looking to understand and trust data. Yet tradtional solutions provide incomplete and inaccurate results

Poor data quality is the single biggest contributor to the poor performance of customer risk-rating models

Poor data quality is the single biggest contributor to the poor performance of customer risk-rating models. Incorrect know-your-customer (KYC) information, missing information on company suppliers, and erroneous business descriptions impair the effectiveness of screening tools and needlessly raise the workload of investigation teams. In many institutions, over half the cases reviewed have been labeled high risk simply due to poor data quality – McKinsey

Data Governance, Customer Experience and a tale of data in the insurance industry

Digital transformation is not a technology problem, but a business imperative, and insurers need to begin to look at their data as a business asset and not simply the domain of the IT department

Data Quality Matters

Enterprise Information management, data, data quality