Ontotext

DECEMBER 1, 2023

So, KGF 2023 proved to be a breath of fresh air for anyone interested in topics like data mesh and data fabric , knowledge graphs, text analysis , large language model (LLM) integrations, retrieval augmented generation (RAG), chatbots, semantic data integration , and ontology building.

Metadata 78

Metadata Sales Consulting Enterprise 78

AWS Big Data

APRIL 17, 2024

Amazon OpenSearch Service recently introduced the OpenSearch Optimized Instance family (OR1), which delivers up to 30% price-performance improvement over existing memory optimized instances in internal benchmarks, and uses Amazon Simple Storage Service (Amazon S3) to provide 11 9s of durability.

Optimization 110

Optimization Snapshot Metadata Cost-Benefit 110

erwin

OCTOBER 8, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (APIs), file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

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. All of the resources are defined in a sample AWS Cloud Development Kit (AWS CDK) template.

Metrics 101

Metrics Visualization Dashboards Interactive 101

CIO Business Intelligence

APRIL 29, 2022

Despite soundings on this from leading thinkers such as Andrew Ng , the AI community remains largely oblivious to the important data management capabilities, practices, and – importantly – the tools that ensure the success of AI development and deployment. Further, data management activities don’t end once the AI model has been developed.

Data Governance 145

Data Governance IT Risk Data Lake 145

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

Ontotext

JANUARY 6, 2021

That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis. You can apply graph optimizations or operations such as traversals and transformations.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

IBM Big Data Hub

SEPTEMBER 20, 2022

Often data scientists aren’t thrilled with the prospect of generating all the documentation necessary to meet ethical and regulatory standards. This is where technology such as IBM FactSheets , can help by reducing the manual labor needed to capture metadata and other facts about a model across stages of the AI lifecycle.

Metadata 57

Metadata Machine Learning Data-driven Modeling 57

Cloudera

FEBRUARY 11, 2019

Cloudera provides a unified platform with multiple data apps and tools, big data management, hybrid cloud deployment flexibility, admin tools for platform provisioning and control, and a shared data experience for centralized security, governance, and metadata management. 3. Expansion beyond core data management.

Management 43

Management Metadata Analytics Machine Learning 43

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

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Consideration of both data & metadata in the migration.

Data Warehouse 85

Data Warehouse Cost-Benefit Metadata Data-driven 85

Alation

JUNE 2, 2022

All Machine Learning uses “algorithms,” many of which are no different from those used by statisticians and data scientists. While ML solves problems with gradient methods (optimization), classic statistical modeling is mostly mathematical equation solving. Recently, Judea Pearl said, “All ML is just curve fitting.” Conclusion.

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

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 71

Metadata Data Lake Machine Learning Management 71

Andrew White

OCTOBER 22, 2021

Data Literacy, training, coordination, collaboration 8. Portfolio Planning/Optimization 5. Data Management Infrastructure/Data Fabric 5. Data Integration tactics 4. Metadata Strategy 3. CDO (data officer) 2. Business Innovation with D&A 6. Specific Vendor Questions 5. Build (SWEL) v Buy 1.

IT 52

IT Data Lake Strategy Data Science 52

Ontotext

MARCH 8, 2023

Here, I will draw upon our own experience from client projects and lessons learned to provide a selection of optimal use cases for knowledge graphs and semantic solutions along with real world examples of their applications. For many organizations, however, the question remains, “Is it the right solution for us?” million users.

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 88

Data Lake Snapshot Metadata Optimization 88

Ontotext

FEBRUARY 7, 2024

However, what we usually don’t talk about when generating an asset, are the huge invisible or unplanned costs occurring at a later stage when the data needs to be made available for analysis or secondary usage. As a result, a big portion of the IT capacity in Pharma is bound by data integration. But that’s not true.

Metadata 52

Metadata Data Integration Measurement Data-driven 52

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 95

Metadata Dashboards Metrics Visualization 95

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 93

Metadata Data Architecture Machine Learning Cost-Benefit 93

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

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. This verbosity allows schema, metadata, and instance data to be in one place, enabling accessibility and manageability.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

AWS Big Data

AUGUST 31, 2023

The Iceberg specification allows seamless table evolution such as schema and partition evolution, and its design is optimized for usage on Amazon S3. Iceberg stores the metadata pointer for all the metadata files. In this post, we use the Yellow taxi public dataset from NYC Taxi & Limousine Commission as our source data.

Data Lake 88

Data Lake Data Warehouse Metadata Data Architecture 88

AWS Big Data

NOVEMBER 29, 2023

Modernizing analytics for scale, performance, and reliability “Our migration from legacy on-premises platform to Amazon Redshift allows us to ingest data 88% faster, query data 3x faster, and load daily data to the cloud 6x faster. Here’s a couple of highlights from this week and for the full list, see below.

Data Warehouse 97

Data Warehouse Data Lake Analytics Machine Learning 97

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.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.) But the implementation of AI is only one piece of the puzzle.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

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. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Metrics Data-driven 52

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 26, 2024

Bad Data Tax and the Data Bill of Rights So far, our discussion has been pretty theoretical, so we need a compelling business justification for moving in this direction. In the race to become data-driven, most efforts have resulted in a tangled web of data integrations and reconciliations across a sea of data silos.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

AWS Big Data

NOVEMBER 29, 2023

Finally, we announced new AI-driven scaling and optimizations for Amazon Redshift Serverless that enable the service to learn from your patterns and proactively scale on multiple dimensions, including concurrent users, data variability, and query complexity. We look forward to seeing what you create!

Data Warehouse 109

Data Warehouse Data Lake Data Integration Dashboards 109

IBM Big Data Hub

JANUARY 17, 2023

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. The data governance capability of a data fabric focuses on the collection, management and automation of an organization’s data. Data integration.

Data-driven 57

Data-driven Enterprise Data Governance Prescriptive Analytics 57

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.

Metadata 52

Metadata Publishing Optimization Testing 52

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

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 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

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

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 88

Metadata Data Lake Optimization Strategy 88