Warning: Creating default object from empty value in /customers/d/8/e/bigdata-doctor.com/httpd.www/wp-content/plugins/accelerated-mobile-pages/includes/options/redux-framework/inc/class.redux_filesystem.php on line 29 Warning: Use of undefined constant AMP_QUERY_VAR - assumed 'AMP_QUERY_VAR' (this will throw an Error in a future version of PHP) in /customers/d/8/e/bigdata-doctor.com/httpd.www/wp-content/plugins/amp/includes/amp-helper-functions.php on line 42 How to set up a Data Innovation Lab

How to set up a Data Innovation Lab

You may also like...

5 Responses

  1. James says:

    Hi! Great post! I work for a French financial institution and we are creating a data exploitation lab but the mandate question is unclear. We are having a lot of friction with the market intelligence department. Even if we work differently, the themes overlapping is big. We are by the way sitting in Technology, as they are. You are hitting the nail on the head!

    • Bigdata Doc Bigdata Doc says:

      Thank you James for your feedback. I think the problem gets worse in larger companies, because the overlapping chances are higher on one hand, and the company is in a position of affording this overlapping… Good luck anyways!

  2. Al says:

    Great work! I like your mission statement but I would add a vision as well… I think it’s important to tell your stakeholders where you are going to be after X months, X years, etc. Don’t you agree?

    • Bigdata Doc Bigdata Doc says:

      Really good feedback! We used to have a vision statement, but in our company, vision statements were a bit devaluated… But again, it is a particularity of our company and I think a vision can add a lot of value for your team as well!

  1. January 19, 2016

    […] You shall play with data and technologies to generate the rights insights at the core of the business Nobody gets it right in one run… prototyping, exploring your data, mining relations between data sources, extracting patterns, etc… all that is a mandatory part of the data science process and data productization. You need to create a Lab environment, where different technologies, algorithms, visualization approaches, etc are tested, prototyped, benchmarked, thrown away in a daily basis (you might get some ideas reading How to setup a Data Innovation Lab) […]

Leave a Reply

Your email address will not be published. Required fields are marked *

Spammers stay away! *