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

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Second, you must establish a definition of “done.” In DataOps, the definition of done includes more than just some working code. Definition of Done. Monitoring Job Metadata.

Testing 152

Testing Metadata Dashboards Statistics 152

Alation

AUGUST 18, 2022

The challenge today is to think more broadly about what these data things could or should be. It’s important to realize that we need visibility into lineage and relationships between all data and data-related assets, including business terms, metric definitions, policies, quality rules, access controls, algorithms, etc.

Metadata 69

Metadata Visualization Statistics Data Architecture 69

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

AWS Big Data

NOVEMBER 7, 2024

BladeBridge offers a comprehensive suite of tools that automate much of the complex conversion work, allowing organizations to quickly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse. Amazon Redshift is a fully managed data warehouse service offered by Amazon Web Services (AWS).

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

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 126

Data Lake Metadata Snapshot Analytics 126

AWS Big Data

JUNE 7, 2023

They chose AWS Glue as their preferred data integration tool due to its serverless nature, low maintenance, ability to control compute resources in advance, and scale when needed. To share the datasets, they needed a way to share access to the data and access to catalog metadata in the form of tables and views.

Metadata 58

Metadata Data Lake Machine Learning Big Data 58

Jen Stirrup

MARCH 29, 2023

SAP helps to solve this search problem by offering ways to simplify business data with a solid data foundation that powers SAP Datasphere. It fits neatly with the renewed interest in data architecture, particularly data fabric architecture. They fail to get a grip on their data.

Data Warehouse 121

Data Warehouse Metadata Data Integration Business Intelligence 121

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 118

Data Lake Data Warehouse Metadata Data Architecture 118

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. The File Manager Lambda function consumes those messages, parses the metadata, and inserts the metadata to the DynamoDB table odpf_file_tracker.

Data Lake 110

Data Lake Data Processing Metadata Snapshot 110

Sisense

JULY 6, 2020

EDM covers the entire organization’s data lifecycle: It designs and describes data pipelines for each enterprise data type: metadata, reference data, master data, transactional data, and reporting data.

Enterprise 98

Enterprise Management Data Architecture Data-driven 98

Octopai

APRIL 20, 2023

Data mesh is an approach to data architecture that is intentionally distributed, where data is owned and governed by domain-specific teams who treat the data as a product to be consumed by other domain-specific teams. What are the principles behind data mesh architecture?

Data-driven 97

Data-driven Data Architecture Sales Interactive 97

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset.

Analytics 110

Analytics Dashboards Metadata Data Warehouse 110

Alation

MAY 31, 2023

This means that specialized roles such as data architects, which focus on modernizing data architecture to help meet business goals, are increasingly important to support data governance. What is a data architect? Their broad range of responsibilities include: Design and implement data architecture.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

erwin

APRIL 16, 2024

The data mesh framework In the dynamic landscape of data management, the search for agility, scalability, and efficiency has led organizations to explore new, innovative approaches. One such innovation gaining traction is the data mesh framework. This empowers individual teams to own and manage their data.

Metadata 52

Metadata Data Quality Data Governance Modeling 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

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

Alation

JANUARY 9, 2023

The Australian Prudential Regulation Authority (APRA) released nonbinding standards covering data risk management. Another agency later also published a legally binding standard to strengthen risk management for financial institutions with specific language related to data architecture and IT infrastructure.

Risk Management 52

Risk Management Risk Management Metadata 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. The data catalog is a foundational layer of the data fabric.

Metadata 52

Metadata IT Data-driven Metrics 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 75

Cost-Benefit Big Data Technology Metadata 75

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

Unstructured Data 64

Unstructured Data Data Lake Data Warehouse Machine Learning 64

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. The Cloud Data Migration Challenge. It’s not a simple definition. Legacy data adds to the challenge.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

IBM Big Data Hub

JULY 5, 2023

Open data formats that kept the data accessible by all but optimized for high performance and with a well-defined structure. Open (sharable) metadata that enables multiple consumption engines or frameworks. Ability to update data (ACID properties) and support transactional concurrency.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

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 53

Modeling Metadata Data Quality Enterprise 53

erwin

FEBRUARY 28, 2024

While the essence of success in data governance is people and not technology, having the right tools at your fingertips is crucial. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52

Ontotext

FEBRUARY 7, 2024

They have to misallocate resources because 80% of the time the data scientists are busy doing data finding, accessing, cleansing, etc. This also results in the information loss I’ve already mentioned and severely impacts our insight creation and monetizing the data. The next element is the variables.

Metadata 52

Metadata Data Integration Data-driven Measurement 52

Alation

JULY 28, 2022

What Are the Biggest Drivers of Cloud Data Warehousing? It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. You really need to understand the metadata and data definitions around different data sets,” Kirsch says.

Data Warehouse 69

Data Warehouse Cost-Benefit Data-driven Data Governance 69

IBM Big Data Hub

JANUARY 18, 2023

Data fabric promotes data discoverability. Here, data assets can be published into categories, creating an enterprise-wide data marketplace. This marketplace provides a search mechanism, utilizing metadata and a knowledge graph to enable asset discovery. Data mesh: A mostly new culture.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

TDAN

JUNE 30, 2020

About a week ago, I was teaching a data modeling class, and an attendee asked me to explain the concept of a data catalog. Like a lot of hype-related terms in IT, there is more than one definition. However, I had recently read the book, The Data Catalog: Sherlock Holmes Data Sleuthing for Analytics by […].

Modeling 52

Modeling Analytics Data Architecture IT 52

AWS Big Data

MARCH 3, 2023

spark_travel_details" limit 10; The table (native Delta table) has been created and updated to the AWS Glue Data Catalog from the EMR Serverless application code. Athena supports reading native Delta tables and therefore we can read the data successfully even though the Data Catalog shows only a single array column.

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

Andrew White

JANUARY 9, 2022

Most of D&A concerns and activities are done within EA in the Info/Data architecture domain/phases. Here too is a blog ( By 2024, 60% of the data used for the de­vel­op­ment of AI and an­a­lyt­ics projects will be syn­thet­i­cally gen­er­ated ) of mine on the topic. There really is not one plan per se for everyone.

Analytics 64

Analytics Measurement Data-driven Modeling 64

AWS Big Data

DECEMBER 20, 2024

Solution overview The basic concept of the modernization project is to create metadata-driven frameworks, which are reusable, scalable, and able to respond to the different phases of the modernization process. These phases are: data orchestration, data migration, data ingestion, data processing, and data maintenance.

Metadata 118

Metadata Data-driven Snapshot Data Lake 118

Jet Global

MAY 1, 2023

Introduction Why should I read the definitive guide to embedded analytics? The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic. It is now most definitely a need-to-have. CRM, ERP, EHR/EMR) or portals (e.g., intranets or extranets). addresses).

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Ontotext

NOVEMBER 11, 2024

Knowledge graphs, while not as well-known as other data management offerings, are a proven dynamic and scalable solution for addressing enterprise data management requirements across several verticals. The RDF-star extension makes it easy to model provenance and other structured metadata. A is B; B is C; C has D; A has D).

Metadata 52

Metadata Knowledge Discovery Data Integration Management 52

AWS Big Data

MAY 12, 2025

Integrating lineage into EMR Serverless AppsFlyer developed a robust solution for column-level lineage collection to provide comprehensive visibility into data transformations across pipelines. Lineage data is stored in Amazon S3 and subsequently ingested into DataHub , AppsFlyers lineage and metadata management environment.

Metrics 82

Metrics Cost-Benefit Metadata Data Lake 82

DataKitchen

AUGUST 8, 2023

Data Observability technology learns what to monitor and provides insights into unforeseen exceptions. However, the market for Data Observability is fragmented and lacks a standard accepted definition, leading to confusion and tool adoption issues. However, there are potential risks and challenges in adopting Data Observability.

Data Quality 130

Data Quality Testing Snapshot Reporting 130