Tag: operationalization
Nov 26, 2019 |
Per research from McKinsey, only 8% of companies successfully scale analytics. To improve this abysmal rate, organizations must conquer what’s been called the last mile of analytics. Read more…
Feb 21, 2019 |
Ask Gartner Research and you’ll find that as of late 2017, 60% of big data projects failed to survive the pilot phase and only 17% of Hadoop deployments went on to the production phase. Read more…
Feb 21, 2018 |
A startup named ParallelM today unveiled new software aimed at alleviating data scientists from the burden of manually deploying, monitoring, and managing machine learning pipelines in production.
Dubbed MLOps, ParallelM‘s software helps to automate many of the operational tasks required to turn a machine learning model from a promising piece of code running nn Spark, Flink, TensorFlow, or PyTorch processing engines into a secure, governed, and production-ready machine learning system. Read more…
Jul 11, 2016 |
You may know TransUnion as one of the credit bureaus that controls the interest rate on your new loan. But in fact the company does much more, and has solutions around fraud detection, collections, and marketing, among others. Read more…
Jun 22, 2016 |
If you’re embarking upon a big data project, then you’re likely running into one or more data management challenges. The decisions you make regarding how you enforce data governance and how you control data flows can make or break your project. Read more…
Jun 9, 2016 |
How do you create business value from data science? It may be easy to answer from a theoretical standpoint, but actually turning data into business value in the real world is another matter entirely. Read more…
Jun 2, 2016 |
It might be a tough word to get out of your mouth, but “operationalization” remains a central element of the big data opportunity. And according to a new Capgemini and Informatica study titled “The Big Data Payoff: Read more…
