IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. After all, Alex may not be aware of all the data available to her.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 83

Data Lake Data Governance Data Architecture Machine Learning 83

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

Alation

FEBRUARY 13, 2020

Why do we need a data catalog? What does a data catalog do? These are all good questions and a logical place to start your data cataloging journey. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. Figure 1 – Data Catalog Metadata Subjects.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

CIO Business Intelligence

APRIL 29, 2022

Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle. Further, data management activities don’t end once the AI model has been developed. era is upon us.

Data Governance 145

Data Governance IT Risk Data Lake 145

bridgei2i

MARCH 11, 2021

The key to taking advantage of AI tools for small businesses is data. Easily understandable, highly curated, and reliable data helps Machine Learning (ML) tools evolve. As long as small businesses don’t have efficient data governance strategies, they can’t properly use AI and ML-powered tools. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. Several factors are driving the adoption of knowledge graphs.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. Do they have a system to manage the metadata for given assets?

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Alation

JUNE 14, 2021

Indeed, automation is a key element to data catalog features, which enhance data security. Selecting a Data Catalog. To support data security, an effective data catalog should have features, like a business glossary, wiki-like articles, and metadata management. And, finding data is only half the battle.

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Digital Transformation 97

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

Metadata 75

Metadata Data Lake Data Processing Data-driven 75

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Cloudera

DECEMBER 15, 2022

With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Only metadata will be regenerated. Newly generated metadata will then point to source data files as illustrated in the diagram below. . Data quality using table rollback.

Metadata 80

Metadata Data Warehouse Snapshot Data Quality 80

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. On the other hand, they don’t support transactions or enforce data quality.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Ontotext

FEBRUARY 12, 2024

In a centralized architecture, data is copied from source systems into a data lake or data warehouse to create a single source of truth serving analytics use cases. This quickly becomes difficult to scale with data discovery and data version issues, schema evolution, tight coupling, and a lack of semantic metadata.

IT 64

IT Metadata Data Quality Data Lake 64

Cloudera

AUGUST 30, 2022

For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Towards Data Science ). Forrester ).

Data Architecture 80

Data Architecture Data Lake Metadata Data Warehouse 80

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. What’s a data mesh?

Management 80

Management Metadata Data Architecture Data Lake 80

Alation

AUGUST 11, 2022

Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. We chatted about industry trends, why decentralization has become a hot topic in the data world, and how metadata drives many data-centric use cases.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

Alation

JULY 19, 2022

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

Metadata 59

Metadata Data Quality Statistics Data Science 59

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

CIO Business Intelligence

DECEMBER 21, 2022

Jim Hare, distinguished VP and analyst at Gartner, says that some people think they need to take all the data siloed in systems in various business units and dump it into a data lake. But what they really need to do is fundamentally rethink how data is managed and accessed,” he says.

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” Iceberg handles massive data born in the cloud.

Metadata 103

Metadata Machine Learning Unstructured Data Data Lake 103

Alation

JUNE 21, 2022

The product concept back then went something like: In a world where enterprises have numerous sources of data, let’s make a thing that helps people find the best data asset to answer their question based on what other users were using. And to determine “best,” we’d ingest log files and leverage machine learning.

Metadata 52

Metadata Data Quality Visualization Data Lake 52

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way.

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

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

Alation

MARCH 21, 2023

When it embarked on a digital transformation and modernization initiative in 2018, the company migrated all its data to AWS S3 Data Lake and Snowflake Data Cloud to provide accessibility to data to all users. Using Alation, ARC automated the data curation and cataloging process. “So

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 45

Big Data Data Lake Internet of Things Enterprise 45

Ontotext

AUGUST 4, 2023

A data fabric utilizes an integrated data layer over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of data across enterprises, including hybrid and multi-cloud platforms. It also helps capture and connect data based on business or domains.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

AWS Big Data

MAY 1, 2024

Solution overview OneData defines three personas: Publisher – This role includes the organizational and management team of systems that serve as data sources. Responsibilities include: Load raw data from the data source system at the appropriate frequency. Provide and keep up to date with technical metadata for loaded data.

Dashboards 111

Dashboards Data-driven Publishing Cost-Benefit 111

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

Andrew White

JANUARY 11, 2021

The data suggests several things: The work of traditional analytics and BI continues towards democratization in the business unit directly, we call this domain analytics in our research, part of domain D&A. Many data science labs are set up as shared services. Data lakes don’t offer this nor should they.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52