O'Reilly on Data

JANUARY 29, 2019

In other words, could we see a roadmap for transitioning from legacy cases (perhaps some business intelligence) toward data science practices, and from there into the tooling required for more substantial AI adoption? On the other hand, we wanted to measure the sophistication of their use of these components.

Deep Learning 209

Deep Learning Machine Learning Data Science Metadata 209

erwin

JANUARY 9, 2020

That’s because it’s the best way to visualize metadata , and metadata is now the heart of enterprise data management and data governance/ intelligence efforts. So here’s why data modeling is so critical to data governance. erwin Data Modeler: Where the Magic Happens.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

CIO Business Intelligence

MARCH 4, 2024

Stakeholders are currently waging an open debate across the industry of centralization versus federated data strategies. Proponents of centralization continue to assert its effectiveness in driving operational efficiencies, enhancing analytics effectiveness, and enabling governance crucial to data security, privacy, and regulatory compliance.

Insurance 89

Insurance Strategy Data Governance Data Integration 89

IBM Big Data Hub

NOVEMBER 4, 2022

This complements IBM’s partnership with MANTA to integrate automated data lineage capabilities from MANTA with IBM Watson Knowledge Catalog on Cloud Pak for Data. Why does data quality matter across the data lifecycle? Data quality issues can have far-reaching consequences across the lifecycle of data: 1.

Data Quality 56

Data Quality Metadata Data Governance Data-driven 56

erwin

JANUARY 17, 2020

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. SQL or NoSQL?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Creating a data architecture roadmap.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

AUGUST 15, 2023

As customers accelerate their migrations to the cloud and transform their businesses, some find themselves in situations where they have to manage data analytics in a multi-cloud environment, such as acquiring a company that runs on a different cloud provider. We use Athena to run queries on data stored on Google Cloud Storage.

Recreation/Entertainment 89

Recreation/Entertainment Unstructured Data Business Intelligence Data-driven 89

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Who are the data owners? Data lineage offers proof that the data provided is reflected accurately.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

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. Enforcing finance regulations has also become a concern for BI & analytics teams.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52

AWS Big Data

MARCH 29, 2024

However, to analyze trends over time, aggregate from different dimensions, and share insights across the organization, a purpose-built business intelligence (BI) tool like Amazon QuickSight may be more effective for your business. With these insights, teams have the visibility to make data integration pipelines more efficient.

Metrics 106

Metrics Visualization Dashboards Interactive 106

Alation

FEBRUARY 13, 2020

This achievement is a testament not only to our legacy of helping to create the data catalog category but also to our continued innovation in improving the effectiveness of self-service analytics. A broader definition of Business Intelligence. Howard Dresner coined the term “Business Intelligence” in 1989.

Business Intelligence 52

Business Intelligence Machine Learning Marketing Metadata 52

datapine

MAY 29, 2019

BI architecture has emerged to meet those requirements, with data warehousing as the backbone of these processes. One of the BI architecture components is data warehousing. What Is Data Warehousing And Business Intelligence? A solid BI architecture framework consists of: Collection of data. Data integration.

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

Cloudera

AUGUST 31, 2021

Data warehousing is the backbone of every data driven organization , providing mission critical analytics. Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Copyright © 2021 Accenture. All rights reserved.

Data Warehouse 85

Data Warehouse Cost-Benefit Metadata Data-driven 85

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

erwin

APRIL 27, 2022

Best Data Modeling Solution (erwin Data Modeler). Read more about erwin® Data Modeler by Quest.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

Octopai

JANUARY 31, 2021

The particular episode we recommend looks at how WeWork struggled with understanding their data lineage so they created a metadata repository to increase visibility. Agile Data. Another podcast we think is worth a listen is Agile Data.

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

Data Virtualization

JANUARY 18, 2024

Reading Time: 3 minutes Today, the most innovative and successful organizations leverage data to increase revenue, minimize expenses, and deliver products and services that meet the needs of their customers. To be truly “data-driven,” an organization must view data as more than a byproduct. The post How to Shop for Data?

Data-driven 59

Data-driven Data Integration Management Metadata 59

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 101

Data Warehouse Data Lake Analytics Machine Learning 101

DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

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

CIO Business Intelligence

MARCH 6, 2024

SAP announced today a host of new AI copilot and AI governance features for SAP Datasphere and SAP Analytics Cloud (SAC). The company is expanding its partnership with Collibra to integrate Collibra’s AI Governance platform with SAP data assets to facilitate data governance for non-SAP data assets in customer environments. “We

Unstructured Data 116

Unstructured Data Dashboards Business Intelligence Data Governance 116

AWS Big Data

SEPTEMBER 7, 2023

We will partition and format the server access logs with Amazon Web Services (AWS) Glue , a serverless data integration service, to generate a catalog for access logs and create dashboards for insights. Both the user data and logs buckets must be in the same AWS Region and owned by the same account.

Metadata 100

Metadata Dashboards Metrics Visualization 100

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Solution overview Apache Iceberg is an open table format for very large petabyte-scale analytic datasets.

Data Lake 94

Data Lake Data Warehouse Metadata Data Architecture 94

erwin

MAY 27, 2020

What, then, should users look for in a data modeling product to support their governance/intelligence requirements in the data-driven enterprise? Nine Steps to Data Modeling. Provide metadata and schema visualization regardless of where data is stored.

Modeling 98

Modeling Metadata Data Governance Visualization 98

CIO Business Intelligence

FEBRUARY 2, 2024

As data and analytics become the beating heart of the enterprise, it’s increasingly critical for the business to have access to consistent, high-quality data assets. Master data management (MDM) is required to ensure the enterprise’s data is consistent, accurate, and controlled.

Management 112

Management Data Governance Cost-Benefit Testing 112

AWS Big Data

NOVEMBER 29, 2023

Of course, the value of a strong data foundation is not new and the need for one spans well beyond generative AI. We also have tools that enable you to act on your data, including Amazon QuickSight for BI, Amazon SageMaker for ML, and of course, Amazon Bedrock for generative AI.

Data Warehouse 109

Data Warehouse Data Lake Data Integration Dashboards 109

Jen Stirrup

MARCH 29, 2023

Put together, these factors help to provide the company with a competitive advantage since better data – and better use of data – leads to better strategies. Data as a product as well as a foundation The data foundation is critical for all types of reporting and analytics. Why is this interesting?

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

IBM Big Data Hub

OCTOBER 12, 2023

Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc. Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model.

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

AWS Big Data

JULY 20, 2023

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale. To overcome these issues, Orca decided to build a data lake.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Enterprise 75

Enterprise Management Strategy Data Lake 75

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 59

Management Enterprise Strategy IT 59

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 52

Management Enterprise Strategy IT 52

Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. How Did the Modern Data Stack Get Started? In the past, data movement was defined by ETL: extract, transform, and load.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

FEBRUARY 21, 2023

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. It is a data modeling methodology designed for large-scale data warehouse platforms.

Data Warehouse 66

Data Warehouse Data Lake Cost-Benefit Metadata 66

CIO Business Intelligence

JUNE 9, 2022

The reporting capabilities enable users to drill down into individual numbers for greater insight using the Analytics 360 platform. They’ve also integrated the tool with Studio, their portal for creating new advertising campaigns. Along the way, metadata is collected, organized, and maintained to help debug and ensure data integrity.

Management 143

Management Advertising Data Lake Sales 143

CIO Business Intelligence

SEPTEMBER 22, 2023

How to choose which DMP is right for your organization While each organization will have its own unique needs, a number of common factors are important to keep in mind when selecting a data management platform. The platform’s data collection, storage, scalability, and processing capabilities will also weigh heavily in making your choice.

Management 103

Management Advertising Data Lake Sales 103