CIO Business Intelligence

JUNE 23, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 93

IT Data Architecture Unstructured Data Big Data 93

AWS Big Data

JUNE 6, 2023

As the SumUp merchants user journey only starts onsite (with a Sign up or product purchase), but extends to offline card reader transactions or usage of our products from within our app and web dashboard, it is important to combine Digital Analytics data with other (backend) data sources in our Data Lake or DWH.

Analytics 56

Analytics Data Lake Testing Optimization 56

The Unofficial Google Data Science Blog

SEPTEMBER 9, 2015

Sawzall is a programming language developed at Google for performing aggregation over the result of complex operations on structured data. Record-level program scope As a data scientist, you write a Sawzall script to operate at the level of a single record. However, it turns out to be quite useful for data science applications.

Data Science 56

Data Science Statistics Testing Metadata 56

AWS Big Data

OCTOBER 25, 2023

Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data.

Unstructured Data 118

Unstructured Data Metadata Management Analytics 118

Peter James Thomas

AUGUST 29, 2018

Additionally I have a direct set of reports who drive the standard solutions around tooling, governance, quality, data protection , Data Ethics , Metadata and data glossary and models. Helping organisations become “data-centric” is a key part of what you do.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

Alation

JULY 19, 2022

As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 117

Data Lake Unstructured Data Data Warehouse Data Quality 117

Cloudera

MAY 17, 2021

Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform. Beyond there being a number of choices each with very different strengths, the parameters for your decision have also changed.

Data Warehouse 89

Data Warehouse Measurement Reporting Testing 89

CIO Business Intelligence

JUNE 14, 2023

Additionally, it is vital to be able to execute computing operations on the 1000+ PB within a multi-parallel processing distributed system, considering that the data remains dynamic, constantly undergoing updates, deletions, movements, and growth. Consider data types.

Unstructured Data 64

Unstructured Data IT Manufacturing Visualization 64

Cloudera

SEPTEMBER 6, 2018

Support machine learning (ML) algorithms and data science activities, to help with name matching, risk scoring, link analysis, anomaly detection, and transaction monitoring. Provide audit and data lineage information to facilitate regulatory reviews. Spark also enables data science at scale. Cloudera Enterprise.

Machine Learning 40

Machine Learning Risk Big Data Unstructured Data 40

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

Machine Learning 261

Machine Learning Software Testing Metadata 261

Cloudera

APRIL 1, 2024

Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics. Our customers run some of the world’s most innovative, largest, and most demanding data science, data engineering, analytics, and AI use cases, including PB-size generative AI workloads.

Unstructured Data 103

Unstructured Data Cost-Benefit Metadata Machine Learning 103