This week’s roundup features articles discussing what to consider when choosing a data science vendor, New Year’s resolutions to help you reach your marketing analytics goals, how to avoid gaps in your analytics strategy, and how nonprofits can benefit from data democratization.

How to Choose a Data Science Vendor

by Nick Ismail, Reporter at Information Age

Data science, big data and AI are current buzzwords, and many companies are rebranding their business intelligence products with these definitions to get a more significant market share. With such a broad offering available it has become difficult to choose the right vendor, and an appropriate structure needs to be put in place as an algorithm to follow during the selection process.


5 New Year’s Resolutions to Refine Your Marketing Analytics Stack

by Rebecca Matias, Business Development Executive at Callbox

According to data compiled by Statistic Brain, people who explicitly set New Year’s resolutions are 10 times more likely to meet their goals than those who don’t bother with resolutions at all. Get insights on practical ideas to help you leverage your marketing analytics stack to its full potential this year.


Blind Spots In Your Marketing Analytics… And What To Do About Them

from Business 2 Community, by Tabitha Jean Naylor, Founder of

The hype around marketing analytics and Big Data has reached a point where you can think it’s your single source of truth. But just because you have the data doesn’t mean you have the full picture. Marketing analytics has several blind spots and it’s important to understand that your analytics is not the end-all-be-all of marketing.


How Nonprofits Can Benefit from the Evolution of Data Democratization

by Becky Land, Business Development Manager at Lityx

Advanced analytics is no longer only accessible to large companies with large budgets, nor is it a responsibility reserved strictly for IT personnel or data scientists. Faced with budgetary constraints and ambitious fundraising targets, nonprofits, in particular, must figure out how to prioritize and implement data-forward strategies.


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