Cloudera

OCTOBER 19, 2023

While navigating so many simultaneous data-dependent transformations, they must balance the need to level up their data management practices—accelerating the rate at which they ingest, manage, prepare, and analyze data—with that of governing this data.

Data-driven 76

Data-driven Data Architecture Predictive Modeling Digital Transformation 76

IBM Big Data Hub

APRIL 11, 2023

Read the AI governance e-book Step one – Evaluate To have their hiring and promotion ecosystems evaluated, organizations should take an active approach by educating its stakeholders on the importance of this process. To prepare for this shift, some organizations are developing a yearly evaluation, mitigation, and review process.

Strategy 87

Strategy Data Architecture Data-driven Testing 87

AWS Big Data

NOVEMBER 13, 2023

For those in the data world, this post provides a curated guide for all analytics sessions that you can use to quickly schedule and build your itinerary. Book your spot early for the sessions you do not want to miss. 11:30 AM – 12:30 PM (PDT) Ceasars Forum ANT318 | Accelerate innovation with end-to-end serverless data architecture.

Analytics 118

Analytics Data Lake Data Warehouse Data-driven 118

AWS Big Data

APRIL 19, 2023

Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights. A modern data architecture is critical in order to become a data-driven organization. Mike is the author of two books and numerous articles.

Technology 105

Technology Data-driven Machine Learning Sales 105

AWS Big Data

DECEMBER 21, 2023

Overview of solution As a data-driven company, smava relies on the AWS Cloud to power their analytics use cases. smava ingests data from various external and internal data sources into a landing stage on the data lake based on Amazon Simple Storage Service (Amazon S3).

Data Lake 114

Data Lake Data Warehouse Data-driven B2B 114

CIO Business Intelligence

FEBRUARY 28, 2024

And not only do companies have to get all the basics in place to build for analytics and MLOps, but they also need to build new data structures and pipelines specifically for gen AI. It quickly adds up in complexity,” says Sheldon Monteiro, EVP at Publicis Sapient, a global digital consultancy. model can handle up to 10 million tokens.

IT 132

IT Consulting Modeling Enterprise 132

Octopai

APRIL 19, 2021

BI teams will have a better handle on their data’s history, its current status, and any changes it may have undergone. Without organized metadata management, the validity of a company’s data is compromised and they won’t achieve adequate compliance, data governance, or generate correct insights. TDWI – David Loshin.

Metadata 59

Metadata Management Business Intelligence Data Governance 59

AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Redshift data warehouses, and third-party and federated data sources. He can be reached via LinkedIn.

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

Alation

JULY 30, 2021

2: Biz Problem – Making Data Ready for Business Analysis. Good, trusted data is no accident; data governance is a crucial prerequisite. As Tom Davenport argues in Analytics at Work, “You can’t be really good at analytics without really good data.” (23). Clean it up before or as part of switching and moving.

Data Warehouse 52

Data Warehouse Data Governance Machine Learning Data-driven 52

Data Virtualization

NOVEMBER 4, 2020

Varian in their book Information Rules. “Technology changes, economic laws do not.” This is one of the most important concepts highlighted in 1994 by Carl Shapiro and Hal R. This simple idea describes the importance of the real effectiveness of.

Internet of Things 52

Internet of Things Technology ROI Digital Transformation 52

TDAN

AUGUST 20, 2019

We hope your Data Management career and programs are progressing well. If you have issues, please refer to DAMA.org for references, as well as the DAMA Data Management Body of Knowledge (DMBok). You can purchase the DMBoK at your favorite book source or via website link. Your DAMA-I Board of […].

Management 40

Management Data Quality Data Architecture Data Governance 40

IBM Big Data Hub

SEPTEMBER 7, 2022

We started the Summer School for Data Leaders five years ago to create a community for data experts to share ideas and relate to people facing similar challenges. Today, the Summer School has grown to include over 400 data leaders across 46 countries and nearly 25 industries.

Data Strategy 52

Data Strategy Strategy Data-driven Data Quality 52

Andrew White

JANUARY 9, 2022

Have a look at this and see if this helps: Data, Analytics and AI Form the Foundation of Data-Driven Decision Making. . Can I book you for a team (DA analytics community) session for 30-40min – with exactly this session ? – Data (and analytics) governance remains a challenge. This was from 2020.

Analytics 64

Analytics Measurement Data-driven Modeling 64

AWS Big Data

DECEMBER 4, 2024

FGAC enables you to granularly control access to your data lake resources at the table, column, and row levels. This level of control is essential for organizations that need to comply with data governance and security regulations, or those that deal with sensitive data. He can be reached via LinkedIn.

Data Lake 118

Data Lake Big Data Management Software 118

AWS Big Data

APRIL 28, 2025

She focuses on crafting cloud-based data platforms, enabling real-time streaming, big data processing, and robust data governance. Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. He is also the author of the book Serverless ETL and Analytics with AWS Glue.

Big Data 66

Big Data Visualization Data Processing Data Processing 66

AWS Big Data

APRIL 28, 2025

She focuses on crafting cloud-based data platforms, enabling real-time streaming, big data processing, and robust data governance. Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. He is also the author of the book Serverless ETL and Analytics with AWS Glue.

Metadata 61

Metadata Data Lake Big Data Publishing 61