IBM Big Data Hub

MARCH 25, 2022

To simplify data access and empower users to leverage trusted information, organizations need a better approach that provides better insights and business outcomes faster, without sacrificing data access controls. The knowledge catalog serves as a library with insights about your data.

Metadata 112

Metadata Data Quality Data Governance Data Integration 112

IBM Big Data Hub

MAY 9, 2023

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. It sounds like a joke, but it’s not, as anyone who has tried to solve business problems with AI may know. We stand on the frontier of an AI revolution.

Enterprise 132

Enterprise Technology Modeling Cost-Benefit 132

Ontotext

JANUARY 10, 2024

The reason is that the inherent complexity of big enterprises is such that this is the simplest model that enables them to “connect the dots” across the different operational IT systems and turn the diversity of their business into a competitive advantage. Often, it’s a by-product of business growth.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

AWS Big Data

OCTOBER 3, 2023

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

Data Lake 100

Data Lake Metadata Snapshot Recreation/Entertainment 100

Ontotext

APRIL 10, 2024

The data ecosystem today is crowded with dazzling buzzwords, all fighting for investment dollars. A survey in 2021 found that a data company was being funded every 45 minutes. Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Testing and Data Observability. Download the 2021 DataOps Vendor Landscape here.

Testing 307

Testing Machine Learning Consulting Data Quality 307

erwin

OCTOBER 8, 2020

So if you’re going to move from your data from on-premise legacy data stores and warehouse systems to the cloud, you should do it right the first time. And as you make this transition, you need to understand what data you have, know where it is located, and govern it along the way. Then you must bulk load the legacy data.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

IBM Big Data Hub

JANUARY 8, 2024

In modern enterprises, where operations leave a massive digital footprint, business events allow companies to become more adaptable and able to recognize and respond to opportunities or threats as they occur. Teams want more visibility and access to events so they can reuse and innovate on the work of others.

Data-driven 78

Data-driven Management Advertising Enterprise 78

IBM Big Data Hub

DECEMBER 19, 2023

As enterprises embrace cloud native and everything as code, the journey from code to production has become a critical aspect of delivering value to customers. The first post in this series navigates the complexities and uncovers the strategies and target state mode for achieving a seamless and effective pathway to deploy.

Testing 80

Testing Enterprise Modeling Software 80

IBM Big Data Hub

NOVEMBER 15, 2023

IBM watsonx is changing the game for enterprises of all shapes and sizes, making it easy for them to embed generative AI into their operations. Watsonx is comprised of three components that empower businesses to customize their AI solutions: watsonx.ai The most common use cases from partners often combine several of these AI tasks.

Sales 91

Sales Software Modeling Enterprise 91

DataKitchen

AUGUST 27, 2021

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

Alation

JANUARY 20, 2022

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Instead, data quality rules promote awareness and trust.

Data Quality 94

Data Quality Data Governance Metrics Statistics 94

AWS Big Data

MARCH 2, 2023

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. AWS Glue 3.0

Data Lake 116

Data Lake Data Processing Metadata Snapshot 116

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 85

Management Metadata Data Architecture Data Lake 85

IBM Big Data Hub

JULY 13, 2022

Data is everywhere in a hybrid and multi-cloud world. Enterprises now have more data, more data tools, and more people involved in data consumption. This data proliferation has made it harder than ever before to trust your data: knowing where it came from, how it has changed, and who is using it.

Metadata 67

Metadata Data Governance Data Quality Data Integration 67

Ontotext

FEBRUARY 12, 2024

Although the enterprise data landscape is littered with new data technology and offerings, the most pressing problem data teams face today isn’t a lack of technology or skills; it’s not knowing how to create a modern data experience. Why Data Mesh?

IT 64

IT Metadata Data Quality Data Lake 64

Ontotext

AUGUST 4, 2023

Generating actionable insights across growing data volumes and disconnected data silos is becoming increasingly challenging for organizations. Working across data islands leads to siloed thinking and the inability to implement critical business initiatives such as Customer, Product, or Asset 360.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

Alation

APRIL 19, 2021

Modern businesses have their heads in the clouds… not that they’re daydreaming. The cloud supports this new workforce, connecting remote workers to vital data, no matter their location. Today, enterprises are migrating to the cloud at a brisk pace. Data Cloud Migration Challenges and Solutions. But why migrate at all?

Cost-Benefit 111

Cost-Benefit Strategy Enterprise Data Strategy 111

IBM Big Data Hub

JULY 25, 2022

Modern-day enterprises face a similar situation regarding data assets. On one side there is a need for data. Businesses ask: “Do we have this kind of data in the enterprise?” “How How do we get that data?” “Can Can I trust that data?” “Can I trust that data?”

Metadata 70

Metadata Enterprise Consulting Publishing 70

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. Both nodes and edges have associated properties modeled as key-values with primitive data types and are single-valued.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL.

Data Lake 101

Data Lake Management Metrics Data Warehouse 101

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

Alation

JANUARY 10, 2023

And implementing a data catalog is no different. From helping analysts search and find the data they need to promoting data as an asset, there are many ways data catalogs can add value to your organisation. Three reasons companies adopt a data catalog. Upgrading an existing catalog.

ROI 52

ROI Data Lake Strategy Data-driven 52

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. When the catalog property s3.delete-enabled Expiration actions – These actions define when objects expire.

Data Lake 83

Data Lake Snapshot Metadata Optimization 83

IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. Using AI for certain business tasks or without guardrails in place may also not align with an organization’s core values.

Risk 75

Risk Modeling Management Metadata 75

IBM Big Data Hub

JUNE 14, 2023

You need to collect, curate, and annotate data for any specific task you want to perform. This is often a very cumbersome exercise that takes significant amount of time to field an AI solution that yields business value. This is usually text, but it can also be code, IT events, time series, geospatial data, or even molecules.

Modeling 90

Modeling Data Lake Enterprise Deep Learning 90

Cloudera

JUNE 2, 2022

Since 2015, the Cloudera DataFlow team has been helping the largest enterprise organizations in the world adopt Apache NiFi as their enterprise standard data movement tool. This need has generated a market opportunity for a universal data distribution service. How to onboard data into their system?

Enterprise 99

Enterprise Data Lake Data Collection Data-driven 99

IBM Big Data Hub

APRIL 28, 2022

Data agility, the ability to store and access your data from wherever makes the most sense, has become a priority for enterprises in an increasingly distributed and complex environment. That’s where the data fabric comes in. enterprises to minimize their time to value.

Metadata 83

Metadata Data Warehouse Forecasting Predictive Modeling 83

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Data Catalog and Master Data Management. Identify Resources.

Management 52

Management Data Quality Metadata Testing 52

Smarten

AUGUST 4, 2023

The Right Self-Serve Data Preparation Solution is Sophisticated, Easy-to-Use and Ensures User Adoption! When your enterprise decides to roll out analytics for business users, it is important to implement the right solution.

Data Lake 52

Data Lake Machine Learning Data Integration Optimization 52

Alation

AUGUST 17, 2022

According to analysts, data governance programs have not shown a high success rate. According to CIOs , historical data governance programs were invasive and suffered from one of two defects: They were either forced on the rank and file — who grew to dislike IT as a result. The Risks of Early Data Governance Programs.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

IBM Big Data Hub

NOVEMBER 28, 2022

Metadata management performs a critical role within the modern data management stack. It helps blur data silos, and empowers data and analytics teams to better understand the context and quality of data. This, in turn, builds trust in data and the decision-making to follow. Improve data discovery.

Metadata 57

Metadata Data Quality Data-driven Data Governance 57

Cloudera

MAY 22, 2023

Data asset standardization is the purposeful and carefully planned consolidation of redundant, contradictory reports, processes, and databases into enterprise standards. Ideally you are realizing these benefits using Cloudera Data Catalog. Archive targeted reports. Repeat the exercise quarterly.

Statistics 74

Statistics Data-driven Reporting Dashboards 74

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. To make confident business decisions, the underlying data needs to be accurate and recent.

Data Quality 93

Data Quality Statistics Data Lake Visualization 93

DataKitchen

AUGUST 8, 2023

On 20 July 2023, Gartner released the article “ Innovation Insight: Data Observability Enables Proactive Data Quality ” by Melody Chien. It alerts data and analytics leaders to issues with their data before they multiply. It alerts data and analytics leaders to issues with their data before they multiply.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

Ontotext

FEBRUARY 12, 2024

In the final part of this three-part series, we’ll explore ho w data mesh bolsters performance and helps organizations and data teams work more effectively. Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59