IBM Big Data Hub

APRIL 15, 2024

Various initiatives to create a knowledge graph of these systems have been only partially successful due to the depth of legacy knowledge, incomplete documentation and technical debt incurred over decades. IBM also developed an accelerator for context-aware feature engineering in the industrial domain.

Manufacturing 92

Manufacturing Contextual Data Knowledge Discovery Data Lake 92

Ontotext

AUGUST 22, 2023

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. As a result, organizations have spent untold money and time gathering and integrating data.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

AWS Big Data

SEPTEMBER 26, 2024

Across industries, this solution unlocks numerous use cases: Research and academia – Summarizing research papers, journals, and publications to accelerate literature reviews and knowledge discovery Legal and compliance – Extracting key information from legal documents, contracts, and regulations to support compliance efforts and risk management Healthcare (..)

Data Lake 108

Data Lake Cost-Benefit Unstructured Data Modeling 108

The Unofficial Google Data Science Blog

JULY 22, 2020

A/B testing isn’t simple just because data is big — the law of large numbers doesn’t take care of everything! Even with big data, A/B tests require thinking deeply and critically about whether or not the assumptions made match the data. Henne, and Dan Sommerfield. 2] Scott, Steven L. 2015): 37-45. [3] ACM, 2017. [4]

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

Domino Data Lab

JUNE 15, 2021

If Big Data has taught us anything, it is that with large volumes and high velocity data, it is advisable to move the computation to where the data resides. Therefore, if we need a value that can be used within the statement or if we need to produce a value for every input row, our best bet is UDFs. About Domino.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

The Unofficial Google Data Science Blog

JANUARY 14, 2016

by AMIR NAJMI Running live experiments on large-scale online services (LSOS) is an important aspect of data science. But the fact that a service could have millions of users and billions of interactions gives rise to both big data and methods which are effective with big data.

Experimentation 42

Experimentation Statistics Metrics Measurement 42

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

We could do this but in our big data world, we would avoid materializing such an inefficient structure by reducing the regression to its sufficient statistics. When solved with an intercept term, regression coefficients for the binary predictors are maximum likelihood estimates for the experiment effects under assumption of additivity.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Ontotext

NOVEMBER 11, 2024

With knowledge graphs, organizations can change, prune, and adapt the schema while keeping the data the same and reusing it to drive even more insights. Years ago, we moved away from the buzzword of Big Data to Smart Data. To make data smart, machines could no longer be bound by inflexible and brittle data schemas.

Metadata 52

Metadata Knowledge Discovery Data Integration Management 52