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. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

erwin

SEPTEMBER 17, 2020

It’s paramount that organizations understand the benefits of automating end-to-end data lineage. Critically, it makes it easier to get a clear view of how information is created and flows into, across and outside an enterprise. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Alation

MARCH 22, 2022

Accenture calls it the Intelligent Data Foundation (IDF), and it’s used by dozens of enterprises with very complex data landscapes and analytic requirements. Simply put, IDF standardizes data engineering processes. They can better understand data transformations, checks, and normalization.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

AWS Big Data

MARCH 13, 2024

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

Analytics 92

Analytics IoT Metadata Internet of Things 92

Ontotext

NOVEMBER 18, 2021

We can kind of do it within one enterprise, agreeing on certain templates, but when we start going cross-enterprise, or when we start integrating legacy data, it will be a lot of work doing that by hand. OntoRefine is a data transformation tool that lets you unite plenty of data formats and get them into your triplestore.

Visualization 98

Visualization Reporting Metadata Enterprise 98

AWS Big Data

APRIL 19, 2023

However, when a data producer shares data products on a data mesh self-serve web portal, it’s neither intuitive nor easy for a data consumer to know which data products they can join to create new insights. This is especially true in a large enterprise with thousands of data products.

Technology 80

Technology Data-driven Machine Learning Sales 80

Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

Metadata 52

Metadata Management Data Governance Machine Learning 52

Octopai

DECEMBER 11, 2022

Commercial enterprises utilized consumer information for marketing without taking appropriate care to keep it private. Let’s take a look at several regulatory standards and explore automated data lineage’s role in smoothing and improving data compliance. Data lineage and financial risk data compliance.

Insurance 52

Insurance Risk Metadata Reporting 52

Cloudera

DECEMBER 9, 2022

Cloudera has been providing enterprise support for Apache NiFi since 2015, helping hundreds of organizations take control of their data movement pipelines on premises and in the public cloud. Developers need to onboard new data sources, chain multiple data transformation steps together, and explore data as it travels through the flow.

Testing 95

Testing Cost-Benefit Interactive Visualization 95

IBM Big Data Hub

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Enterprise 80

Enterprise Data Integration Data Quality Contextual Data 80

AWS Big Data

JANUARY 17, 2024

This allows you to simplify security and governance over transactional data lakes by providing access controls at table-, column-, and row-level permissions with your Apache Spark jobs. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 91

Data Lake Snapshot Big Data Data-driven 91

AWS Big Data

NOVEMBER 16, 2023

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault. Data Vault 2.0

Enterprise 83

Enterprise Data Warehouse Data Lake Optimization 83

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 is used extensively for data publishing and data interchange and is based on W3C and other industry standards.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Alation

AUGUST 11, 2022

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. But, through it all, Mohan says it’s critical to view everything through the same lens: gaining business value from data. Data fabric is a technology architecture.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. This allows you to scale all analytics and AI workloads across the enterprise with trusted data. 

Cost-Benefit 84

Cost-Benefit Metadata Optimization Management 84

erwin

MARCH 4, 2021

Instead, he suggests they put data governance in real-world scenarios to answer these questions: “What is the problem you believe data governance is the answer to?” Or “How would you recognize having effective data governance in place?”. The Benefits of erwin Data Intelligence. Where is it?

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

AWS Big Data

OCTOBER 11, 2023

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. The Data Catalog now contains references to the machine-readable data. Use the Data Catalog and transform the hospital price transparency data.

Visualization 94

Visualization Dashboards Data-driven Gap analysis 94

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 83

Data Lake Data Architecture Metadata Data Warehouse 83

Octopai

NOVEMBER 23, 2020

In fact, the LIBOR transition program marks one of the largest data transformation obstacles ever seen in financial services. Building an inventory of what will be affected is a huge undertaking across all of the data, reports, and structures that must be accounted for. Automated Data Lineage for Your LIBOR Project.

Metadata 54

Metadata Enterprise Business Intelligence Data Governance 54

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise. IBM watsonx.ai

Machine Learning 67

Machine Learning Data Warehouse Modeling Cost-Benefit 67

Alation

JANUARY 17, 2023

Data governance is a key use case of the modern data stack. Who Can Adopt the Modern Data Stack? The modern data stack is well-suited for companies with large amounts of data. These help data analysts visualize key insights that can help you make better data-backed decisions.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Octopai

JANUARY 19, 2021

With Octopai’s support and analysis of Azure Data Factory, enterprises can now view complete end-to-end data lineage from Azure Data Factory all the way through to reporting for the first time ever.

Metadata 52

Metadata ROI Optimization Data Quality 52

erwin

APRIL 16, 2024

In this blog, we’ll delve into the critical role of governance and data modeling tools in supporting a seamless data mesh implementation and explore how erwin tools can be used in that role. erwin also provides data governance, metadata management and data lineage software called erwin Data Intelligence by Quest.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 77

Enterprise Data Warehouse Reporting Metadata 77

Rocket-Powered Data Science

MARCH 20, 2023

We could further refine our opening statement to say that our business users are too often in a state of being data-rich, but insights-poor, and content-hungry. This is where we dispel an old “big data” notion (heard a decade ago) that was expressed like this: “we need our data to run at the speed of business.”

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

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 predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 101

Data Lake Management Metrics Data Warehouse 101

Cloudera

OCTOBER 11, 2021

Modak’s Nabu is a born in the cloud, cloud-neutral integrated data engineering platform designed to accelerate the journey of enterprises to the cloud. The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata.

Data Lake 89

Data Lake Cost-Benefit Data-driven Dashboards 89

Alation

JULY 18, 2022

To ensure you can deliver on this world-changing vision of data, Alation helps you maximize the value of your data lake with integrations to the Unity catalog. Alation will leverage the Databricks Unity Catalog so users can easily integrate metadata from multiple workspaces, powering discovery, governance, and insights inside Alation.

ROI 52

ROI Metadata Data Lake Digital Transformation 52

AWS Big Data

JANUARY 27, 2023

To build a data-driven business, it is important to democratize enterprise data assets in a data catalog. With a unified data catalog, you can quickly search datasets and figure out data schema, data format, and location. For metadata read/write, Flink has the catalog interface.

Data Lake 61

Data Lake Metadata Business Analysis Data-driven 61

CIO Business Intelligence

AUGUST 3, 2023

And at First Commerce Bank, EVP and COO Gregory Garcia hopes to leverage unified, real-time data to monitor risks such as worsening vacancy rates that could make it harder for commercial property owners to pay their mortgages.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

Ontotext

FEBRUARY 12, 2024

As organizations become more data-driven, different use cases will always require different types of transformations, putting a heavy load on the centralized teams. For large enterprises, data mesh distributes data ownership and reduces dependencies between services.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

IBM Big Data Hub

JULY 5, 2023

This was, without a question, a significant departure from traditional analytic environments, which often meant vendor-lock in and the inability to work with data at scale. Another unexpected challenge was the introduction of Spark as a processing framework for big data. Comprehensive data security and data governance (i.e.

Data Lake 67

Data Lake Metadata Cost-Benefit Data Warehouse 67

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. Introduction. CRM platforms).

Data Processing 88

Data Processing Data Warehouse Enterprise Visualization 88

Jet Global

JULY 19, 2023

Data Connectivity Enhancements Data and content authors are the first users in the app building infrastructure and content. It is important for our customers to access advanced connectors and data transformation features so they can build a robust data layer.

Dashboards 52

Dashboards Visualization Reporting Interactive 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MARCH 14, 2024

Microsoft recently introduced a comprehensive analytics solution for its enterprise customers, Microsoft Fabric. The solution offers data movement, data science, real-time analytics, and business intelligence within a single platform.

Analytics 52

Analytics Management Reporting Enterprise 52