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. The response times for these data sources are critical to our key stakeholders.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

erwin

OCTOBER 8, 2020

But even with the “need for speed” to market, new applications must be modeled and documented for compliance, transparency and stakeholder literacy. With all these diverse metadata sources, it is difficult to understand the complicated web they form much less get a simple visual flow of data lineage and impact analysis.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

AWS Big Data

NOVEMBER 29, 2023

This includes tools to help you customize your foundation models, and new services and features to build a strong data foundation to fuel your generative AI applications. Customizing foundation models The need for data is quite obvious if you are building your own foundation models (FMs).

Data Warehouse 111

Data Warehouse Data Lake Data Integration Dashboards 111

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Then, you transform this data into a concise format.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

AWS Big Data

FEBRUARY 21, 2023

Data warehouses are mostly built using the dimensional model approach, which has consistently met business needs. Additionally, scalability of the dimensional model is complex and poses a high risk of data integrity issues. What is a dimensional data model?

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

CIO Business Intelligence

APRIL 29, 2022

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Many organisations focus too heavily on fine tuning their computational models in their pursuit of ‘quick-wins.’

Data Governance 145

Data Governance IT Risk Data Lake 145

Ontotext

FEBRUARY 26, 2024

However, it still requires more effort than building a single-purpose graph, like a labeled property graph (LPG), where you can whiteboard your graph model in an hour. Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. We call this the “bad data tax.”

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Cloudera

MARCH 23, 2022

Figure 1: Apache Iceberg fits the next generation data architecture by abstracting storage layer from analytics layer while introducing net new capabilities like time-travel and partition evolution. #1: Apache Iceberg enables seamless integration between different streaming and processing engines while maintaining data integrity between them.

Metadata 90

Metadata Data Architecture Machine Learning Cost-Benefit 90

IBM Big Data Hub

JANUARY 5, 2023

Next generation of big data platforms and long running batch jobs operated by a central team of data engineers have often led to data lake swamps. Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g.,

Metadata 123

Metadata Cost-Benefit Enterprise Interactive 123

Cloudera

JUNE 6, 2019

While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Now the admins need to synchronize multiple copies of the data and metadata and ensure that users across the many clusters are not viewing stale information.

Metadata 86

Metadata Data Lake Optimization Strategy 86

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. If you want more control over and more value from all your data, join us for a demo of erwin MM.

Data Governance 40

Data Governance Risk Metadata Management 40

Andrew White

OCTOBER 22, 2021

Monetization/Link data to outcome (value pyramid) business value of data/business impact 20. Business Information Model/Arch compared to classic enterprise data model and how to relate it to catalogs and marketplaces and enterprise data models 13. Data Management Infrastructure/Data Fabric 5.

IT 52

IT Data Lake Strategy Data Science 52

AWS Big Data

FEBRUARY 2, 2023

Since its launch in 2006, Amazon Simple Storage Service (Amazon S3) has experienced major growth, supporting multiple use cases such as hosting websites, creating data lakes, serving as object storage for consumer applications, storing logs, and archiving data. For Report path prefix , enter cur-data/account-cur-daily.

Reporting 84

Reporting Data Lake Management Optimization 84

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. As a result, alternative data integration technologies (e.g.,

Data Processing 91

Data Processing Data Warehouse Enterprise Visualization 91

Data Virtualization

JUNE 22, 2023

The Denodo Platform is a logical data management platform, powered by. The post Denodo Joins Forces with Presto appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Integration 52

Data Integration Management Data Lake Metadata 52

Ontotext

MARCH 8, 2023

With the size of data and dropping attention spans of online users, digital personalization has become one of the top priorities for companies’ business models. As such, most large financial organizations have moved their data to a data lake or a data warehouse to understand and manage financial risk in one place.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 52

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. in lieu of simply landing in a data lake.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

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.

Management 89

Management Metadata Data Architecture Data Lake 89

Alation

JANUARY 13, 2022

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

Data Lake 59

Data Lake Metadata Data-driven Data Governance 59

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 84

Cost-Benefit Metadata Data Governance Modeling 84

erwin

AUGUST 31, 2023

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. A: It always was and is getting cooler!!

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift empowers users to extract powerful insights by securely and cost-effectively analyzing data across data warehouses, operational databases, data lakes, third-party data stores, and streaming sources using zero-ETL approaches.

Data Warehouse 98

Data Warehouse Machine Learning Data-driven Data Lake 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 65

Data Architecture Data Lake Machine Learning Data Governance 65

erwin

JULY 17, 2019

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. Digital Transformation Strategy: Smarter Data.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52