CIO Business Intelligence

MARCH 24, 2023

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Ontotext

AUGUST 22, 2023

Context: The Key to Making Data Useful It goes without saying that data without meaning can yield incorrect insights, leading to potentially dangerous decisions. Beyond that, and without a way to visualize, connect, and utilize the data, it’s still just a bunch of random information. How to Get a Semantic Edge?

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

erwin

MAY 27, 2020

What’s desperately needed is a way to understand the relationships and interconnections between so many entities in data sets in detail. Visualizing data from anywhere defined by its context and definition in a central model repository, as well as the rules for governing the use of those data elements, unifies enterprise data management.

Modeling 98

Modeling Metadata Data Governance Visualization 98

AWS Big Data

NOVEMBER 22, 2023

Many AWS customers adopted Apache Hudi on their data lakes built on top of Amazon S3 using AWS Glue , a serverless data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development.

Data Lake 100

Data Lake Snapshot Metadata Optimization 100

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

AWS Big Data

JUNE 10, 2024

When evolving such a partition definition, the data in the table prior to the change is unaffected, as is its metadata. Only data that is written to the table after the evolution is partitioned with the new definition, and the metadata for this new set of data is kept separately. SparkActions.get().expireSnapshots(iceTable).expireOlderThan(TimeUnit.DAYS.toMillis(7)).execute()

Data Lake 116

Data Lake Metadata Snapshot Analytics 116

Jen Stirrup

MARCH 29, 2023

However, to turn data into a business problem, organizations need support to move away from technical issues to start getting value as quickly as possible. SAP Datasphere simplifies data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface. Why is this interesting?

Data Warehouse 121

Data Warehouse Metadata Data Integration Business Intelligence 121

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 94

Metadata Data Lake Visualization Data Transformation 94

Alation

JANUARY 13, 2022

Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Data fabric has captured most of the limelight; it focuses on the technologies required to support metadata-driven use cases across hybrid and multi-cloud environments. We’ll dig into this definition in a bit.

Data Lake 59

Data Lake Metadata Data-driven Data Governance 59

Alation

AUGUST 11, 2022

We chatted about industry trends, why decentralization has become a hot topic in the data world, and how metadata drives many data-centric use cases. But, through it all, Mohan says it’s critical to view everything through the same lens: gaining business value from data. Data fabric is a technology architecture.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

CIO Business Intelligence

OCTOBER 26, 2023

To earn your CBIP certification, you’ll need two or more years of full-time experience in CIS, data modeling, data planning, data definitions, metadata systems development, enterprise resource planning, systems analysis, application development, and programming or IT management.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

Ontotext

FEBRUARY 7, 2024

However, what we usually don’t talk about when generating an asset, are the huge invisible or unplanned costs occurring at a later stage when the data needs to be made available for analysis or secondary usage. As a result, a big portion of the IT capacity in Pharma is bound by data integration.

Metadata 52

Metadata Data Integration Measurement Data-driven 52

Alation

JANUARY 25, 2022

Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. 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. Data Catalog: To access and represent all metadata types.

Metadata 52

Metadata IT Metrics Data-driven 52

Ontotext

JULY 29, 2021

KGs bring the Semantic Web paradigm to the enterprises, by introducing semantic metadata to drive data management and content management to new levels of efficiency and breaking silos to let them synergize with various forms of knowledge management. Take this restaurant, for example. Enterprise Knowledge Graphs and the Semantic Web.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

AWS Big Data

AUGUST 31, 2023

Iceberg stores the metadata pointer for all the metadata files. When a SELECT query is reading an Iceberg table, the query engine first goes to the Iceberg catalog, then retrieves the entry of the location of the latest metadata file, as shown in the following diagram. The following example demonstrates this.

Data Lake 100

Data Lake Data Warehouse Metadata Data Architecture 100

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. This verbosity allows schema, metadata, and instance data to be in one place, enabling accessibility and manageability.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

Ontotext

JULY 13, 2023

Knowledge graphs have greatly helped to successfully enhance business-critical enterprise applications, especially those where high performance tagging and agile data integration is needed. Enterprises generate an enormous amount of data and content every minute. How can you build knowledge graphs for enterprise applications?

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

AWS Big Data

OCTOBER 25, 2024

The metadata of the YARN metrics collected in Amazon S3 is created, stored, and represented as database and tables in AWS Glue Data Catalog , which is in turn available to Amazon Athena for further processing. The solution needs Athena to run queries against the data from the CUR using standard SQL. Choose Next.

Metrics 80

Metrics Cost-Benefit Reporting Optimization 80

datapine

MAY 29, 2019

BI architecture has emerged to meet those requirements, with data warehousing as the backbone of these processes. But first, let’s start with basic definitions. Each of that component has its own purpose that we will discuss in more detail while concentrating on data warehousing. Data integration. Storage of data.

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

Ontotext

JANUARY 6, 2021

That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis. Knowledge graphs help with data analysis in a number of ways.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. If you want more control over and more value from all your data, join us for a demo of erwin MM.

Data Governance 40

Data Governance Risk Metadata Management 40

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. In terms of data lineage, they offer an excellent definition here. .

Data Governance 83

Data Governance Data Processing Data Quality Metadata 83

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.

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Metadata 65

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Smart DwH Mover helps in accelerating data warehouse migration.

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

AWS Big Data

JUNE 12, 2023

Acting as a bridge between producer and consumer apps, it enforces the schema, reduces the data footprint in transit, and safeguards against malformed data. AWS Glue is an ideal solution for running stream consumer applications, discovering, extracting, transforming, loading, and integrating data from multiple sources.

Management 80

Management Metadata Testing Internet of Things 80

CIO Business Intelligence

SEPTEMBER 22, 2023

Data management platform definition A data management platform (DMP) is a suite of tools that helps organizations to collect and manage data from a wide array of first-, second-, and third-party sources and to create reports and build customer profiles as part of targeted personalization campaigns.

Management 105

Management Advertising Data Lake Sales 105

AWS Big Data

OCTOBER 11, 2023

The data ingestion process copies the machine-readable files from the hospitals, validates the data, and keeps the validated files available for analysis. Data analysis – In this stage, the files are transformed using AWS Glue and stored in the AWS Glue Data Catalog.

Visualization 104

Visualization Dashboards Data-driven Gap analysis 104

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. Enabling workers to find the right data is crucial to promoting self-service analytics.

Business Intelligence 52

Business Intelligence Machine Learning Marketing Metadata 52

Ontotext

MAY 30, 2019

There are two reasons for this: First, Linked Data, or, to put it in Plain English, the practice of explaining the meaning of content to machines, is essentially about linking content to semantically modeled data. Second, Linked Data is creating highly connected, computer-processable definitions of entities.

Cost-Benefit 87

Cost-Benefit Big Data Technology Metadata 87

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. However, it offers two extremely valuable business benefits: reducing data redundancy and improving data integrity.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

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. Definition and Descriptions.

Data Governance 84

Data Governance Machine Learning Metadata Data Science 84

Ontotext

MAY 30, 2019

There are two reasons for this: First, Linked Data, or, to put it in Plain English, the practice of explaining the meaning of content to machines, is essentially about linking content to semantically modeled data. Second, Linked Data is creating highly connected, computer-processable definitions of entities.

Cost-Benefit 75

Cost-Benefit Technology Big Data Metadata 75

Alation

JULY 28, 2022

Data discovery and relationship mapping are among the top ways to achieve high value from any kind of data warehouse. You really need to understand the metadata and data definitions around different data sets,” Kirsch says. But you must be tough!”.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

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 Machine Learning 52

Alation

JANUARY 17, 2023

What if, experts asked, you could load raw data into a warehouse, and then empower people to transform it for their own unique needs? Today, data integration platforms like Rivery do just that. By pushing the T to the last step in the process, such products have revolutionized how data is understood and analyzed.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Andrew White

JANUARY 9, 2022

Much as the analytics world shifted to augmented analytics, the same is happening in data management. You can find research published on the infusion of ML in data quality, and also data catalogs, data discovery, and data integration. I suspect there is much less Maverick to synthetic data today.

Analytics 64

Analytics Measurement Data-driven Modeling 64

erwin

JULY 17, 2019

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. You need automated data mapping and cataloging through the integration lifecycle process, inclusive of data at rest and data in motion.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98