Do you need a Harvard degree to run a business ?

The other day I was at my mechanic's shop for the annual inspection of my vehicle.

This is one of those small garages you can still find in towns, with his owner in blue overalls, friendly and yet a bit gruff.

His shop works great. He has two assistants who are hard workers like him and always smiling. You can see that everything here runs smoothly, without stress. The garage is clean and organized, and from experience I know that his customers are delighted with his services.

So I asked him what was the secret of his success.


Warning : You're losing money by not using data virtualization

You think your organization does all the right things when it comes to data management and your 50+ databases are well documented according to your DBA (DataBase Administrator). So why worry ?

Well, a DBA is indeed more than able to handle the technical issues of data storage, access and security, but what about the actual usage your organization makes of the data ?


DataBook : A year in review (2015)

What was new for DataBook in 2015 ?

At Rever, we are constantly working in order to improve our products. Always with two fundamentals in mind : customer satisfaction and innovation. As our softwares continue to evolve, we were able to offer several new initiatives in 2015.

Here's a recap of what happened last year for our data virtualization tool DataBook which we were very proud to present to the world in its newly improved version !

Version 1.2 [March 30, 2015] :


What is DataBook ?

Do you need to virtualize your data ?

DataBook, what is it ?

  • My data :

 the way I want  : 

- I collect them according to my needs, even if they're scattered across separate databases
- I name them as I please
- I rearrange them as per my own rules

 whenever I want  :


Data lifecycle management, what is it anyway ?

DLM or ILM ?

What is Data lifecycle management (or DLM for short) ? It's about handling data's full lifecycle inside an information system : from their creation to their deletion (or archiving) when they become obsolete. Data lifecycle management could be defined as the group of processes implemented in order to manage the enterprise's data from their definition to their retrieval ("technical" point of view). For instance, a typical question in DLM would be "When can you archive a particular datum ?". 


Distilling your data into valuable information

Analogy between a whisky distillery and data management

The similitudes don't typically jump out, do they? But you'll quickly see the point. 

On one side, in a whisky distillery we have engineers who build the tubings and alembics and such (the containers), and biologists who are in charge of taking care of the many processes leading to the final product (the content). It's all about measuring the quality and tasting.

Once bottled, the blend of whisky goes to meet the world (and be enjoyed by happy consumers).


Metadata for dummies

Metadata are data describing other data (semantically data about data). It's the information which allows to recognize the collected data. For example the most common metadata are the backup date, the size and author of a file... all the information allowing you to identify and locate the data in due time (it can be a document, an audio file, an image, in theory any kind of collected information).


The single most important skill you must have to steer data towards value creation

The world of data is at a cross-road. On one hand of the spectrum, several big industries such as finance or healthcare are broadening their traditional ways of using data. And « data » is the buzz word of 2014 in human resources with companies increasingly looking for data miners, data analysts, data engineers and so on. But on the other hand, organisations globally are still on the fences about investing in data and many countries lack basic training in data management.

Subscribe to RSS - data management