Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). Most of the data management moved to back-end servers, e.g., databases.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

datapine

NOVEMBER 19, 2019

In business intelligence, we are evolving from static reports on what has already happened to proactive analytics with a live dashboard assisting businesses with more accurate reporting. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

Domino Data Lab

JULY 22, 2019

But the business logic kept getting more and more progressively rolled back into the middle layer, also called application servers, web servers, later being called middleware. Then in the bottom tier, you had your data management, your back office, right? That was the origin of big data. Then things changed.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Smart Data Collective

OCTOBER 14, 2019

Regardless of if you’re a data science professional or an IT department who wants to help your company have more successful data science projects, it’s essential to have some data science tools under your belt to avail of when needed. It allows secure and interactive SQL analytics at the petabyte scale.

Data Science 67

Data Science Machine Learning Big Data Interactive 67

Cloudera

NOVEMBER 19, 2020

The Public Sector data challenge. Robust online systems have streamlined interactions and generated a wealth of new data to support mission success and enhanced citizen engagements. However, this rapid scaling up of data across government agencies brings with it new challenges. Fraudulent Activity Detection.

Machine Learning 114

Machine Learning Data-driven Modeling Deep Learning 114

Alation

APRIL 14, 2022

A useful feature for exposing patterns in the data. Supports the ability to interact with the actual data and perform analysis on it. A cloud environment with such features will support collaboration across departments and across common data types, including csv, JSON, XML, AVRO, Parquet, Hyper, TDE, and more. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

AWS Big Data

OCTOBER 26, 2023

At this relatively small scale of 100 GB, queries in this benchmark run on Redshift Serverless in an average of a few seconds, which is representative of what users loading an interactive BI dashboard would expect. Aamer Shah is a Senior Engineer in the Amazon Redshift Service team.

Data Warehouse 99

Data Warehouse Cost-Benefit Dashboards Optimization 99

O'Reilly on Data

MAY 21, 2019

Here are some typical ways organizations begin using machine learning: Build upon existing analytics use cases: e.g., one can use existing data sources for business intelligence and analytics, and use them in an ML application. Use ML to unlock new data types—e.g., A typical data pipeline for machine learning.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238