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

Alation

MAY 19, 2022

Establish what data you have. Active metadata gives you crucial context around what data you have and how to use it wisely. Active metadata provides the who, what, where, and when of a given asset, showing you where it flows through your pipeline, how that data is used, and who uses it most often.

Metadata 52

Metadata Data Analytics Analytics Data Governance 52

Ontotext

JANUARY 29, 2024

In 2023, data leaders and enthusiasts were enamored of — and often distracted by — initiatives such as generative AI and cloud migration. Without this, organizations will continue to pay a “bad data tax” as AI/ML models will struggle to get past a proof of concept and ultimately fail to deliver on the hype.

Strategy 52

Strategy Management Metadata Data-driven 52

CIO Business Intelligence

NOVEMBER 22, 2022

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Failing to meet these needs means getting left behind and missing out on the many opportunities made possible by advances in data analytics.”

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Alation

AUGUST 30, 2022

Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. We had data but no data intelligence and, as a result, insights remained hidden or hard to come by. This universe of metadata represents a treasure trove of connected information.

Metadata 52

Metadata Data Quality Data Governance Machine Learning 52

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

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

MAY 1, 2024

Excel-based data utilization Microsoft Excel is available on almost everyone’s PC in the company, and it helps lower the hurdles when starting to utilize data. However, Excel is mainly designed for spreadsheets; it’s not designed for large-scale data analytics and automation.

Dashboards 111

Dashboards Data-driven Publishing Cost-Benefit 111

IBM Big Data Hub

JANUARY 17, 2023

The rise of cloud object storage has driven the cost of storage down and new technologies have evolved to access and query the data stored in there more efficiently. A data lakehouse platform takes advantage of the low-cost storage and leverages the latest query engine to provide warehouse-like performance.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 94

Data Lake Unstructured Data Data Warehouse Data Quality 94

AWS Big Data

DECEMBER 18, 2023

AWS Step Functions is a fully managed visual workflow service that enables you to build complex data processing pipelines involving a diverse set of extract, transform, and load (ETL) technologies such as AWS Glue , Amazon EMR , and Amazon Redshift. There are multiple tables related to customers and order data in the RDS database.

Metadata 121

Metadata Visualization Data Lake Data-driven 121

erwin

FEBRUARY 4, 2021

So what’s holding organizations back from fully using their data to make better, smarter business decisions? Data Governance Bottlenecks. It uncovered a number of obstacles that organizations have to overcome to improve their data operations. Overcoming Data Governance Bottlenecks.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

erwin

JANUARY 30, 2020

The results of our new research show that organizations are still trying to master data governance, including adjusting their strategies to address changing priorities and overcoming challenges related to data discovery, preparation, quality and traceability. Most have only data governance operations.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

AWS Big Data

JULY 20, 2023

Orca connects to your environment in minutes with patented SideScanning technology to provide complete coverage across vulnerabilities, malware, misconfigurations, lateral movement risk, weak and leaked passwords, overly permissive identities, and more. In addition, we describe the Orca Platform architecture and the technologies used.

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

CIO Business Intelligence

MARCH 4, 2024

To deliver a cohesive data strategy, seamless data access and sharing requires the breaking down of data silos. This is where data fabric tools with their focus on orchestration, contextual layering, and metadata management are important elements to add to the equation. To learn more, visit us here.

Insurance 77

Insurance Strategy Data Governance Data Integration 77

datapine

JANUARY 31, 2022

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. Ultimately, business intelligence and analytics are about much more than the technology used to gather and analyze data. Let’s look at our first use case.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Smart Data Collective

OCTOBER 13, 2021

There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. This is something that you can learn more about in just about any technology blog. We would like to talk about data visualization and its role in the big data movement.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

IBM Big Data Hub

JUNE 8, 2022

However, a foundational step in evolving into a data-driven organization requires trusted, readily available, and easily accessible data for users within the organization; thus, an effective data governance program is key. Here are a few common data management challenges: Regulatory compliance on data use.

Data-driven 56

Data-driven Enterprise Data Governance Data Lake 56

Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. Security: It must serve data throughout a system.

Data Governance 85

Data Governance Metadata Data-driven Enterprise 85

Ontotext

JANUARY 26, 2023

KnowWhereGraph is a location-centric knowledge graph of data at the interface between humans and the environment, based on existing standards like RDF, OWL and GeoSPARQL. Motivating the use of knowledge graph technology for environmental data, the authors explain why spatial data requires special treatment.

Interactive 52

Interactive Metadata Data Integration Data-driven 52

Alation

OCTOBER 5, 2021

However, about 50% of those surveyed also admit that they do not assess, monitor, or measure their data governance systems. Perhaps even more alarming: fewer than 33% expect to exceed their returns on investment for data analytics within the next two years. Data governance and AI.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 77

Cost-Benefit Metadata Optimization Management 77

AWS Big Data

NOVEMBER 6, 2023

The following graph describes a simple data quality check pipeline using setup and teardown tasks. Airflow will cache variables and connections locally so that they can be accessed faster during DAG parsing, without having to fetch them from the secrets backend, environments variables, or metadata database.

Metrics 103

Metrics Metadata Snapshot Management 103

Andrew White

JANUARY 11, 2021

So the material is not designed for IT – but spans business and technology. The fill report is here: Leadership Vision for 2021: Data and Analytics. How do you think Technology Business Management plays into this strategy? Where does the Data Architect role fits in the Operational Model ? Product Management.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Ontotext

NOVEMBER 18, 2021

Picture this – you start with the perfect use case for your data analytics product. And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own.

Visualization 98

Visualization Reporting Metadata Enterprise 98

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

CIO Business Intelligence

MARCH 29, 2022

. • You have data but don’t use it. Why does valuable data so often go unused? Lack of annotation with the right metadata is a contributing factor. An even larger issue is that people may not know how to see value in data. Recognizing what data can tell you is an acquired skill for people beyond just data scientists.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. Data science and MLOps. Start a trial.

Data-driven 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56

BI-Survey

FEBRUARY 6, 2020

Today’s data-literate users want governed and scalable self-service BI functions to answer critical business questions and to get the most out of their data assets. Technological innovations and their increasing proliferation are shaping enterprise reporting and BI. Data management has always been a challenge for companies.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

Ontotext

JUNE 22, 2023

On top of that, data is sometimes unreliable , and inaccurate or missing metadata makes it hard to decide which information to trust. It facilitates finding information and exploring it visually and enables deeper data analytics based on graph and AI algorithms.

Metrics 52

Metrics Statistics Visualization Metadata 52

Andrew White

MARCH 22, 2019

to weave together the governance and management of master data, application data, and less-widely shared data, and just enough enterprise metadata management. Your Future Requires You to Define Your Real Master Data. Data and analytics (and maybe AI) are getting very tired terms.

Analytics 68

Analytics Metadata Data Governance Management 68

AWS Big Data

JUNE 6, 2023

SumUp is a leading global financial technology company driven by the purpose of leveling the playing field for small businesses. Data Catalog: We also wanted to automate a Glue Crawler to have metadata in a Data Catalog and be able to explore our files in S3 with Athena.

Analytics 55

Analytics Data Lake Testing Optimization 55

O'Reilly on Data

MARCH 31, 2020

You might have millions of short videos , with user ratings and limited metadata about the creators or content. Job postings have a much shorter relevant lifetime than movies, so content-based features and metadata about the company, skills, and education requirements will be more important in this case.

Management 327

Management Machine Learning Experimentation Metrics 327

Andrew White

JANUARY 9, 2022

Which trends do you see for 2022 in AI & ML technology and tools and tool capabilities? – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend. I would take a look at our Top Trends for Data and Analytics 2021 for additional AI, ML and related trends. .

Analytics 64

Analytics Measurement Modeling Data-driven 64