CIO Business Intelligence

NOVEMBER 4, 2022

We’ll work with those scientists and actually build the computer models and go run it, and it can be anything from sub-physical particle imaging to protein folding,” he says. “In In other cases, it’s more of a standard computational requirement and we help them provide the data in the right formats.

Data Lake 102

Data Lake IT Experimentation Data-driven 102

O'Reilly on Data

OCTOBER 19, 2021

Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 342

IT Testing Experimentation Software 342

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 78

Data Science Data Analytics Prescriptive Analytics Analytics 78

erwin

JULY 17, 2019

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. Digital Transformation Strategy: Smarter Data.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. After all, Alex may not be aware of all the data available to her.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52