Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. All this while the platform serves as the core foundation providing metadata and governance capabilities across these workloads.

Management 43

Management Metadata Analytics Machine Learning 43

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

AWS Big Data

MARCH 29, 2024

Analyzing historical patterns allows you to optimize performance, identify issues proactively, and improve planning. You can slice data by different dimensions like job name, see anomalies, and share reports securely across your organization. The sample dashboard showed metrics over time, top errors, and comparative job analytics.

Metrics 104

Metrics Visualization Dashboards Interactive 104

IBM Big Data Hub

JANUARY 5, 2023

Both approaches were typically monolithic and centralized architectures organized around mechanical functions of data ingestion, processing, cleansing, aggregation, and serving. 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

Cloudera

AUGUST 31, 2021

Data warehousing is the backbone of every data driven organization , providing mission critical analytics. Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Copyright © 2021 Accenture. All rights reserved.

Data Warehouse 81

Data Warehouse Cost-Benefit Metadata Data-driven 81

AWS Big Data

MAY 16, 2024

With the new REST API, you can now invoke DAG runs, manage datasets, or get the status of Airflow’s metadata database, trigger, and scheduler—all without relying on the Airflow web UI or CLI. This comes at the cost of running more web server instances, which is a trade-off between cost-optimization and responsiveness.

Testing 89

Testing Interactive Metrics Management 89

Alation

JUNE 2, 2022

In part two of this series, I’ll dive more deeply into AI/ML and data lineage, in the cloud and otherwise, and discuss how data governance and security can support these critical use cases, wherever they reside. Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

AWS Big Data

FEBRUARY 1, 2023

This introduces the need for both polling and pushing the data to access and analyze in near-real time. From an operational standpoint, we designed a new shared responsibility model for data ingestion using AWS Glue instead of internal services (REST APIs) designed on Amazon EC2 to extract the data.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

JUNE 7, 2023

Through their unique position in ports, at sea, and on roads, they optimize global cargo flows and create sustainable customer value. Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. An AWS Glue job (metadata exporter) runs daily on the source account.

Metadata 55

Metadata Data Lake Machine Learning Big Data 55

Andrew White

OCTOBER 22, 2021

Business Information Model/Arch compared to classic enterprise data model and how to relate it to catalogs and marketplaces and enterprise data models 13. Analytics Tactics (known outcome/known data/BI/analytics v unknown outcome/unknown data/data science/ML) 11. Data Hub Strategy 10.

IT 52

IT Data Lake Strategy Data Science 52

AWS Big Data

FEBRUARY 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. MongoDB Atlas is a developer data service from AWS technology partner MongoDB, Inc.

Metadata 74

Metadata Data Lake Machine Learning Management 74

AWS Big Data

NOVEMBER 29, 2023

This cloud service was a significant leap from the traditional data warehousing solutions, which were expensive, not elastic, and required significant expertise to tune and operate. Amazon Redshift Serverless, generally available since 2021, allows you to run and scale analytics without having to provision and manage the data warehouse.

Data Warehouse 100

Data Warehouse Data Lake Analytics Machine Learning 100

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

NOVEMBER 22, 2023

Hudi provides tables , transactions , efficient upserts and deletes , advanced indexes , streaming ingestion services , data clustering and compaction optimizations, and concurrency control , all while keeping your data in open source file formats. This effectively provides change streams to enable incremental data pipelines.

Data Lake 92

Data Lake Snapshot Metadata Optimization 92

AWS Big Data

MAY 21, 2024

During implementation, the LINQ team worked with OpenSearch Service specialists to optimize the OpenSearch Service cluster configuration to maximize performance and optimize cost of the solution. This results in an optimized record for each product for quick and efficient search in OpenSearch Service.

Manufacturing 96

Manufacturing Sales Optimization Data Processing 96

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Solution overview Apache Iceberg is an open table format for very large petabyte-scale analytic datasets.

Data Lake 92

Data Lake Data Warehouse Metadata Data Architecture 92

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: 1: Multi-function analytics . Although this allows for schema evolution, it poses a problem if the table has too many changes.

Metadata 91

Metadata Data Architecture Machine Learning Cost-Benefit 91

AWS Big Data

SEPTEMBER 7, 2023

We will partition and format the server access logs with Amazon Web Services (AWS) Glue , a serverless data integration service, to generate a catalog for access logs and create dashboards for insights. Both the user data and logs buckets must be in the same AWS Region and owned by the same account.

Metadata 99

Metadata Dashboards Metrics Visualization 99

DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

AWS Big Data

SEPTEMBER 29, 2023

Analyzing XML files can help organizations gain insights into their data, allowing them to make better decisions and improve their operations. Analyzing XML files can also help in data integration, because many applications and systems use XML as a standard data format. This approach optimizes the use of your XML files.

Metadata 65

Metadata Visualization Data-driven Optimization 65

Andrew White

JANUARY 9, 2022

On Thursday January 6th I hosted Gartner’s 2022 Leadership Vision for Data and Analytics webinar. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend. So in summary they are very similar concepts but data fabric seems to be the more rounded of the two.

Analytics 64

Analytics Measurement Modeling Data-driven 64

AWS Big Data

JULY 20, 2023

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale. To overcome these issues, Orca decided to build a data lake.

Data Lake 87

Data Lake Analytics Snapshot Optimization 87

IBM Big Data Hub

OCTOBER 12, 2023

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. Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model.

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Modeling 76

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. RDF facilitates strategic integration while LPGs are best for tactical analytics. We use them every day without realizing.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

AWS Big Data

NOVEMBER 29, 2023

We also have tools that enable you to act on your data, including Amazon QuickSight for BI, Amazon SageMaker for ML, and of course, Amazon Bedrock for generative AI. It does all of this while factoring in your price/performance targets so you can optimize between cost and performance.

Data Warehouse 109

Data Warehouse Data Lake Dashboards Data Integration 109

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. Our goal is to demonstrate the foundational role of the data catalog, and how it influences the higher corresponding layers that form an effective data fabric.

Metadata 52

Metadata IT Metrics Data-driven 52

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

erwin

MAY 27, 2020

What, then, should users look for in a data modeling product to support their governance/intelligence requirements in the data-driven enterprise? Nine Steps to Data Modeling. Provide metadata and schema visualization regardless of where data is stored. naming and database standards, formatting options, and so on.

Modeling 98

Modeling Metadata Data Governance Visualization 98

Ontotext

FEBRUARY 23, 2023

The engines must facilitate the advanced data integration and metadata data management scenarios where an EKG is used for data fabrics or otherwise serves as a data hub between diverse data and content management systems. This era is over! billion edges.

Publishing 52

Publishing Metadata Optimization Testing 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 integration. Start a trial.

Data-driven 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56

Ontotext

FEBRUARY 26, 2024

They allow you to connect the dots across your data and progress on the spectrum toward knowledge, insight, and wisdom. For this reason, graph technologies have taken center stage in the data and analytics space as a critical enabler. Before you can really maximize the value from data, you must first connect the dots.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

erwin

FEBRUARY 4, 2021

Points of integration. Without an accurate, high-quality, real-time enterprise data pipeline, it will be difficult to uncover the necessary intelligence to make optimal business decisions. So what’s holding organizations back from fully using their data to make better, smarter business decisions? Regulations.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

AWS Big Data

OCTOBER 11, 2023

The data in the machine-readable files can provide valuable insights to understand the true cost of healthcare services and compare prices and quality across hospitals. The availability of machine-readable files opens up new possibilities for data analytics, allowing organizations to analyze large amounts of pricing data.

Visualization 96

Visualization Dashboards Data-driven Gap analysis 96

Ontotext

JULY 29, 2021

KGs bring the Semantic Web paradigm to the enterprises, by introducing semantic metadata to drive data management and content management to new levels of efficiency and breaking silos to let them synergize with various forms of knowledge management. Take this restaurant, for example. Enterprise Knowledge Graphs and the Semantic Web.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

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 Strategy Optimization 86

AWS Big Data

FEBRUARY 21, 2023

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. What is a dimensional data model? It optimizes the database for faster data retrieval.

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Metadata 65

Ontotext

SEPTEMBER 2, 2020

Instead, it creates a unified way, sometimes called a data fabric, of accessing an organization’s data as well as 3rd party or global data in a seamless manner. Data is represented in a holistic, human-friendly and meaningful way. For efficient drug discovery, linked data is key.

Insurance 72

Insurance Metadata Publishing Unstructured Data 72