Octopai

MARCH 24, 2020

Let’s start with automated tools that foster the seamless interaction of multiple metadata best practices, such as data discovery, data lineage and the use of a business glossary. Here is an overview of how automated metadata management makes your business intelligence smarter. Watch the webinar!

Metadata 43

Metadata Cost-Benefit Business Intelligence ROI 43

Octopai

JUNE 15, 2020

With the insurance company’s current data architecture, the process would have no chance of being completed in time for the change. Watch our webinar to hear how your peers are doing it! Download the webinar. Automated Data Lineage Reduces Total Time to a Fraction. Impact Analysis Research in 1 Day Instead of 100?

Insurance 52

Insurance Metadata Business Intelligence Data Warehouse 52

Cloudera

FEBRUARY 14, 2024

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. Expiring snapshots is a relatively cheap operation and uses metadata to determine newly unreachable files.

Strategy 56

Strategy Optimization Snapshot Metadata 56

Octopai

JULY 12, 2020

After all, how do you adjust this month’s operations based on last month’s data if it takes two weeks to finally receive the information you need? This is exactly how Octopai customer, Farm Credit Services of America (FCSA) , felt when their BI team needed to modernize their data warehouse.

Data Warehouse 58

Data Warehouse Data Quality Metadata Risk Management 58

erwin

MAY 2, 2022

Data modeling is a serious scientific method with many rules and best practices. One must also capture the vast quantity of metadata around the OLTP business requirements that must be reflected. I was pricing a data warehousing project with just 4 TB of data – small by today’s standards. Related links: Like this blog?

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

Alation

APRIL 25, 2023

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Cloudera

MAY 22, 2018

With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. save the built model container, along with metadata like who built or deployed it. Simplified user administration.

Data Science 41

Data Science Snapshot Machine Learning Metadata 41

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. We will publish follow up blogs for other data services. Read why the future of data lakehouses is open.

Data Warehouse 79

Data Warehouse Snapshot Metadata Cost-Benefit 79

Alation

APRIL 25, 2023

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

Jet Global

JUNE 17, 2021

So while the process of gathering data and establishing metadata to support transfer pricing would be highly standardized, the new system would have flexibility built in from the start to accommodate inevitable change. Adopting Key Principles. I'd like to see a demo of insightsoftware solutions.

Risk 98

Risk Recreation/Entertainment Forecasting Manufacturing 98

Cloudera

FEBRUARY 8, 2024

Cloudera Data Warehouse (CDW) running Hive has previously supported creating materialized views against Hive ACID source tables. release and the matching CDW Private Cloud Data Services release, Hive also supports creating, using, and rebuilding materialized views for Iceberg table format.

Snapshot 88

Snapshot Metadata Cost-Benefit Data Warehouse 88

Cloudera

JULY 13, 2023

In this blog, we will discuss performance improvement that Cloudera has contributed to the Apache Iceberg project in regards to Iceberg metadata reads, and we’ll showcase the performance benefit using Apache Impala as the query engine. Impala can access Hive table metadata fast because HMS is backed by RDBMS, such as mysql or postgresql.

Metadata 70

Metadata Snapshot Data Warehouse Statistics 70

Cloudera

DECEMBER 15, 2022

With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Only metadata will be regenerated. Newly generated metadata will then point to source data files as illustrated in the diagram below. . Data quality using table rollback. Metadata management .

Metadata 77

Metadata Data Warehouse Snapshot Data Quality 77

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Forrester ).

Data Architecture 77

Data Architecture Data Lake Metadata Data Warehouse 77

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Metrics Data-driven 52

Alation

AUGUST 11, 2021

To answer this question, I recently joined Anthony Seraphim of Texas Mutual Insurance Company (TMIC) and David Stodder of TDWI on a webinar. The three of us talked migration strategy and the best way to move to the Snowflake Data Cloud. This makes sense: knowing your data and who can access it is a critical first step before any move.

Data Governance 52

Data Governance Insurance Metadata Strategy 52

Jet Global

MAY 1, 2023

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. Metadata Self-service analysis is made easy with user-friendly naming conventions for tables and columns. addresses). Use in-depth show-and-tell.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Alation

FEBRUARY 20, 2020

According to the report, “Demand for data catalogs is soaring as organizations struggle to inventory distributed data assets to facilitate data monetization and conform to regulations.” The tour stops at Gartner Symposium next month, where you can learn first hand why Gartner believes “Data Catalogs are the New Black.”.

Machine Learning 52

Machine Learning Metadata Reporting Data-driven 52