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

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 78

Data Lake Data Architecture Data-driven Data Warehouse 78

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 132

Enterprise Cost-Benefit Unstructured Data Software 132

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

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 60

Unstructured Data Data Lake Data Warehouse Machine Learning 60

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

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 133

Metrics KPI IT Consulting 133

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

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 60

Big Data Data Architecture Enterprise Data Science 60

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 73

Data Quality Metrics Visualization Dashboards 73

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

CIO Business Intelligence

APRIL 29, 2022

Data has rights and sovereignty. Data Security: Achieving authentication, access control, and encryption without negatively impacting productivity. Data Ingestion and Processing: Ensuring that data quality, streaming, and transformation capabilities support your decision-making needs.

Digital Transformation 128

Digital Transformation Strategy Data-driven Data Strategy 128

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

Sisense

SEPTEMBER 3, 2020

This includes database modeling, metrics definition, dashboard design , and creating and publishing executive reports. ROI (return on investment) is also a key concern, as business analysts apply their data-related activities to finance, marketing, and risk management, for instance. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

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

Jen Stirrup

AUGUST 25, 2020

It is hard to get a definitive answer. However, you still need to think properly about data. Again, putting the data into Azure SQL Database and then Power BI allows for more Business Intelligence scenarios to be implemented, such as time series. Perception. Please feel free to contact me.

Advertising 67

Advertising Business Intelligence Data Processing Data Architecture 67

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

AWS Big Data

JANUARY 24, 2023

It contains references to data that is used as sources and targets in AWS Glue ETL (extract, transform, and load) jobs, and stores information about the location, schema, and runtime metrics of your data. The Data Catalog organizes this information in the form of metadata tables and databases.

Data Architecture 68

Data Architecture Metadata Data Lake Snapshot 68

AWS Big Data

JUNE 29, 2023

With Amazon Redshift, you can analyze your data to derive holistic insights about your business and your customers. In many organizations, one or multiple Amazon Redshift data warehouses run daily for data and analytics purposes.

Data Warehouse 61

Data Warehouse Dashboards Testing Visualization 61

BizAcuity

APRIL 6, 2022

There is no definite answer. Data warehousing, data integration and BI systems: The KPIs and data architecture that crypto casinos need to track alter slightly from what regular onlines casinos keep track of. Gaming enthusiasts are seeing the perks offered by NFT games DEALI including passive income through gaming.

Data Analytics 52

Data Analytics Analytics B2B Deep Learning 52

Cloudera

AUGUST 22, 2021

In fact, the definition of ‘cloud’ has changed so much over the years. As mentioned earlier, an enterprise data strategy can help companies do more with their data, which outlines the need for a cloud-native hybrid data architecture (known as enterprise data cloud) that is able to leverage data in this heterogeneous landscape.

Cost-Benefit 103

Cost-Benefit Strategy IoT ROI 103

AWS Big Data

OCTOBER 10, 2023

In this post, we check for the PERSON_NAME and EMAIL data types. If any columns with sensitive data are detected, it persists the sensitive data detection results to the S3 bucket. AWS Glue Data Quality uses Data Quality Definition Language (DQDL) to author the data quality rules.

Data Quality 94

Data Quality Data Governance Data Lake Testing 94

Jim Harris

JANUARY 1, 2016

No matter how uncomfortable these discussions may be at times, they are essential to evaluating the potential ROI of data quality improvements, defining data quality standards, and most importantly, providing a working definition of success. No, you don’t need a folk singer, but you may need an executive sponsor.

Data Quality 61

Data Quality Data Governance Cost-Benefit ROI 61

AWS Big Data

APRIL 24, 2023

It allows you to access diverse data sources, build business intelligence dashboards, build AI and machine learning (ML) models to provide customized customer experiences, and accelerate the curation of new datasets for consumption by adopting a modern data architecture or data mesh architecture.

Data Lake 82

Data Lake Data Governance Cost-Benefit Machine Learning 82

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

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 94

Data Lake Data Processing Metadata Snapshot 94

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

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 97

Data Lake Data Warehouse Metadata Data Architecture 97

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

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 127

IT Consulting Modeling Enterprise 127

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