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

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

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 77

Data-driven Data Architecture Sales Modeling 77

Peter James Thomas

AUGUST 2, 2019

It includes 30 new definitions, some of which have been contributed by people like Tenny Thomas Soman, George Firican, Scott Taylor and and Taru Väre. Data Architecture – Definition (2). Data Catalogue. Data Sourcing. Geospatial Data. Reference Data (contributor: George Firican ).

Analytics 69

Analytics Data Analytics Data Architecture Statistics 69

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 81

Data Lake Data Architecture Data-driven Data Warehouse 81

DataKitchen

DECEMBER 20, 2020

The agile alliance definition of business agility consists of two parts. The DataOps Engineering skillset includes hybrid and cloud platforms, orchestration, data architecture, data integration, data transformation, CI/CD, real-time messaging, and containers. Companies that move slowly get left behind. .

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

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

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. When can you declare it done?

Testing 152

Testing Metadata Dashboards Statistics 152

erwin

JUNE 19, 2020

Despite the similarities in name, there are a number of key differences between an enterprise architecture and solutions architecture. Much like the differences between enterprise architecture (EA) and data architecture, EA’s holistic view of the enterprise will often see enterprise and solution architects collaborate.

Enterprise 130

Enterprise Data Architecture Strategy Data Governance 130

TDAN

MAY 4, 2021

When you’ve been involved in data management for as long as I have, things are definitely bound to change. And things have changed, quite a lot, in fact. Back when I started in IT, IMS was the primary database system used at most big enterprises and most of the computing was done on mainframe systems. […].

Enterprise 139

Enterprise Management Data Architecture IT 139

CIO Business Intelligence

NOVEMBER 1, 2023

SAP doesn’t want to build those tools from scratch itself: “We definitely want to leverage what’s already out there,” Sun said, noting there are already many large language models (LLMs) it can build on, adding its own prompting, fine tuning, and data embedding to get those models to business customers quickly.

Enterprise 125

Enterprise Cost-Benefit Unstructured Data Software 125

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 Strategy 98

erwin

JUNE 25, 2020

The Difference Between Technical Architecture and Enterprise Architecture. We previously have discussed the difference between data architecture and EA plus the difference between solutions architecture and EA. Organizations can try erwin Evolve for free and keep any content you produce should you decide to buy.

Enterprise 144

Enterprise Data Architecture Data-driven Cost-Benefit 144

erwin

JUNE 19, 2020

Despite the similarities in name, there are a number of key differences between an enterprise architecture and solutions architecture. Much like the differences between enterprise architecture (EA) and data architecture, EA’s holistic view of the enterprise will often see enterprise and solution architects collaborate.

Enterprise 94

Enterprise Data Architecture Strategy Data Governance 94

Ontotext

JULY 9, 2020

There is no easy answer to these questions but we still need to make sense of the data around us and figure out ways to manage and transfer knowledge with the finest granularity of detail. Knowledge graphs, the ones with semantically modeled data even more so , allow for such a granularity of detail.

Data Architecture 128

Data Architecture Unstructured Data Enterprise Technology 128

erwin

JANUARY 9, 2020

From regulatory compliance and business intelligence to target marketing, data modeling maintains an automated connection back to the source. Building a more agile and governable data architecture: Create and implement common data design standards from the start. erwin Data Modeler: Where the Magic Happens.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

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

AUGUST 31, 2023

This enables you to easily manage and maintain your tables on transactional data lakes. This provides the flexibility to manage analytics at scale and find the most cost-effective architecture solution. The following example demonstrates this. We hope this gives you a great starting point for querying Iceberg tables in Amazon Redshift.

Data Lake 95

Data Lake Data Warehouse Metadata Data Architecture 95

erwin

OCTOBER 24, 2019

. • Harvesting data – Automate the collection of metadata from various data management silos and consolidate it into a single source. Structuring and deploying data sources – Connect physical metadata to specific data models, business terms, definitions and reusable design standards.

Metadata 104

Metadata Management Data-driven Data Architecture 104

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 62

Unstructured Data Data Lake Data Warehouse Machine Learning 62

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. Use the odpf_setup_test_data_glue_job_s3_policy.json policy definition. Use the odpf_setup_test_data_glue_job_ddb_policy.json policy definition.

Data Lake 93

Data Lake Data Processing Metadata Snapshot 93

Anmut

APRIL 6, 2023

How do you do a Data Maturity Assessment? What does a Data Maturity Assessment Measure? What makes a Good Data Maturity Assessment? What is a Data Maturity Assessment? The definition of a data maturity assessment is a measurement of the reliability, effectiveness, and efficiency of an organisation’s data management.

Cost-Benefit 52

Cost-Benefit Data Quality Data Governance Measurement 52

IBM Big Data Hub

JUNE 28, 2023

With Amazon Omics awareness of file formats like FASTQ, BAM and CRAM, clients can focus on data, bring in workflow definition tools like WDL, letting Amazon Omics take care of the rest. This process alone saves hundreds of hours of productive time.

Informatics 63

Informatics Consulting Cost-Benefit Data Architecture 63

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.

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

CIO Business Intelligence

JUNE 27, 2022

By now, most enterprises have reached data maturity. “If If your company has data, you’re definitely leveraging it and trying to use insights from analytics to drive positive business outcomes,” says John Loury, president and CEO of Cause + Effect Strategy, a business intelligence consulting firm.

Metrics 128

Metrics KPI IT Consulting 128

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 91

Data Lake Data Warehouse Data-driven B2B 91

Cloudera

JULY 27, 2021

Considering the stack – as we say in Cloudera, from Edge to AI – there are certain elements particularly in ingestion, cleansing and data engineering, as well as in storage and warehousing, that lend themselves to on-premise deployments, either for networking, cost or regulatory reasons. So we’re delighted to be a part of the story.

Big Data 62

Big Data Data Architecture Enterprise Data Science 62

IBM Big Data Hub

JANUARY 25, 2023

Breaking down these silos to encourage data access, data sharing and collaboration will be an important challenge for organizations in the coming years. The right data architecture to link and gain insight across silos requires the communication and coordination of a strategic data governance program.

Data Governance 52

Data Governance Data-driven Strategy Management 52

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

AWS Big Data

JUNE 6, 2023

On the Crawlers page, select data-quality-result-crawler and choose Run. When the crawler is complete, you can see the AWS Glue Data Catalog table definition. After you create the table definition on the AWS Glue Data Catalog, you can use Athena to query the Data Catalog table. Choose Create crawler.

Data Quality 74

Data Quality Metrics Visualization Dashboards 74

CIO Business Intelligence

FEBRUARY 28, 2024

And not only do companies have to get all the basics in place to build for analytics and MLOps, but they also need to build new data structures and pipelines specifically for gen AI. All of that is fascinating to us and my team is definitely working on this,” she adds. This is imperative for us to do.”

IT 107

IT Consulting Modeling Enterprise 107

Anmut

MARCH 24, 2022

In this post, we’ll explore what a data landscape is, why it’s so important, and how you can design and build a data landscape that supports your business goals. What is a data landscape? The definition of data landscape differs depending on the context and who you ask. Focus on value.

ROI 52

ROI Measurement Data-driven Data Transformation 52

TDAN

JUNE 18, 2019

Most organizations agree that they have data issues, categorized as data quality. Organizations typically define the scope of their data problems by their current (known) data quality issues (symptoms). However, this definition is […].

Data Quality 90

Data Quality Data Architecture IT Data Strategy 90

Ontotext

MARCH 27, 2024

People often assume that RDF graphs are harder to develop, because one must develop schema and should deal with namespace definitions for the identifiers. Nodes in an LPG do not differentiate between data types like classes and categories. They provide relationship detection between data elements but lack uniformity of nomenclature.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

IBM Big Data Hub

DECEMBER 4, 2023

According to Oracle , best practices for the planning process include five categories of information: Project definition: This is the blueprint that will include relevant information for an implementation project. Oracle provides a variety of templates to facilitate item definition as data is catalogued and moved to the cloud.

Testing 74

Testing Consulting Digital Transformation Cost-Benefit 74

Cloudera

AUGUST 9, 2022

The DRRA focuses on describing how to think about reliability, resiliency, and recovery for the Cloudera Data Platform, and is a living document describing our collected learning across the platform and across customers. . Understanding and planning for disaster recovery is the next step in the process towards a modern data architecture.

Data Lake 77

Data Lake Data Warehouse Data-driven IoT 77

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