article thumbnail

Thermo Fisher transforms its customer experience

CIO Business Intelligence

With its business rapidly growing and customer expectations rising, Thermo Fisher Scientific is turning to machine learning and robotic process automation (RPA) to transform the customer experience. Since 2006, it has grown with additional mergers and acquisitions, including Life Technologies Corp. Catalyzing change.

IT 105
article thumbnail

Wolverine hits pause for cloud success

CIO Business Intelligence

It’s one of those CIO-plus roles that people talk about,” says Slater, who has served as CIO since 2006. Wolverine relies on seven data centers, two of which are run by third-party partners. To that end, the company plans to start creating a data lake in 2023, she says. We are not currently doing that.”.

Data Lake 109
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

At AstraZeneca, data and AI are more than game changers – they are life changers

CIO Business Intelligence

The goal, she explained, is to knock down data silos between those groups, using multiple data lakes supported by strong security and governance, to drive positive impact across the supply chain, manufacturing, and the clinical trials of new drugs. . Four ways to improve data-driven business transformation .

article thumbnail

How The Cloud Made ‘Data-Driven Culture’ Possible | Part 1

BizAcuity

2006: Amazon spearheads the cloud initiative, drops EC2 and S3 into the market. 2007: Amazon launches SimpleDB, a non-relational (NoSQL) database that allows businesses to cheaply process vast amounts of data with minimal effort. Hadoop was developed in 2006. Amazon launches AWS (but no cloud solutions yet). The pain point?

article thumbnail

Analyze Amazon S3 storage costs using AWS Cost and Usage Reports, Amazon S3 Inventory, and Amazon Athena

AWS Big Data

Since its launch in 2006, Amazon Simple Storage Service (Amazon S3) has experienced major growth, supporting multiple use cases such as hosting websites, creating data lakes, serving as object storage for consumer applications, storing logs, and archiving data. This could be your data lake or application S3 bucket.

article thumbnail

Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations.

article thumbnail

AWS re:Invent Recap: The Future of Cloud

Alation

It’s only been 15 years since AWS took the first steps to the cloud with S3 and EC2, which launched in 2006. How do you provide access and connect the right people to the right data? AWS has created a way to manage policies and access, but this is only for data lake formation. What about other data sources?