Octopai

JUNE 1, 2020

Data mapping is the cornerstone of many important business intelligence processes: Data Integration – Even if systems are compatible, combining two disparate data repositories still requires meticulous data mapping. Correct data mapping facilitates the creation of usable, searchable data warehouses.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52

Alation

APRIL 14, 2023

Last week, the Alation team had the privilege of joining IT professionals, business leaders, and data analysts and scientists for the Modern Data Stack Conference in San Francisco. In “The modern data stack is dead, long live the modern data stack!” Cloud costs are growing prohibitive.

Data Warehouse 52

Data Warehouse Data-driven Digital Transformation Metadata 52

erwin

APRIL 27, 2022

In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis. Change Data Capture identifies and processes only the data that has changed and stores the changed data in a form so as to be of further use.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

Alation

JULY 28, 2022

The cloud is no longer synonymous with risk. There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. But today, there is a magic quadrant for cloud databases and warehouses comprising more than 20 vendors. What do you migrate, how, and when?

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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. Webcast: Build better data models.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 100

Data Warehouse Data Lake Analytics Machine Learning 100

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Those days are long gone if they ever existed.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model?

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Then, you transform this data into a concise format.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.)

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses. Let’s summarize very quickly.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

erwin

JULY 17, 2019

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. Your organization won’t be able to take complete advantage of analytics tools to become data-driven unless you establish a foundation for agile and complete data management.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Jet Global

JUNE 17, 2021

Managing Data Integrity. Before rolling the new process out, the company needed to address data integrity, a normal stage in any new software implementation project. Following the data integrity phase, the company focused on setting up the correct processes and on rightsizing the project.

Risk 98

Risk Recreation/Entertainment Forecasting Manufacturing 98

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MAY 1, 2023

CEO Priorities Grow revenue and “hit the number” Manage costs and meet profitability goals Attract and retain talent Innovate and out-perform the competition Manage risk Connect the Dots Present embedded analytics as a way to differentiate from the competition and increase revenue. Present your business case.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

JUNE 9, 2022

Access to these updated views enables your teams to be more self-sufficient and lowers the risk associated with view regeneration. Seamless Integration with Cloud Data Warehouse Targets. Expect simplified access to high-quality, extensible views of ERP data for reporting and analytics in a cloud-native destination.

Operational Reporting 52

Operational Reporting Reporting Data Warehouse Cost-Benefit 52