Cloudera

JUNE 25, 2021

The Replication Manager support matrix is documented in our public docs. This blog post outlines detailed step by step instructions to perform Hive Replication from an on-prem CDH cluster to a CDP Public Cloud Data Lake. CDP Data Lake cluster versions – CM 7.4.0, CDP Data Lake cluster versions – CM 7.4.0,

Data Lake 69

Data Lake Metadata Unstructured Data Management 69

Ontotext

FEBRUARY 12, 2024

This calls for additional planning, documentation, and testing. A data mesh will likely require more engineers to get started, so a critical mass is needed for successful adoption. Each team should be accountable for providing their prepared data sets to downstream systems. For instance, JPMorgan Chase & Co.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

CIO Business Intelligence

DECEMBER 4, 2023

Tomorrow’s market leaders will recognize how to curate and enrich the value of all assets, which will train AI models, generate insights, and drive automation. The ways modern data is used, processed, and analyzed are continuously evolving as machine learning technology becomes better at these tasks. Structure/Operationalize.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

erwin

OCTOBER 31, 2019

What data do we have and where is it? Data is a critical asset used to operate, manage and grow a business. While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

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 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

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

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

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. However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 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

Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

AWS Big Data

SEPTEMBER 26, 2023

AWS Lake Formation helps you centrally govern, secure, and globally share data for analytics and machine learning. With Lake Formation, you can manage access control for your data lake data in Amazon Simple Storage Service (Amazon S3 ) and its metadata in AWS Glue Data Catalog in one place with familiar database-style features.

Data Lake 67

Data Lake Metadata Management Modeling 67

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Text, images, audio, and videos are common examples of unstructured data. Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly.

Unstructured Data 118

Unstructured Data Metadata Management Analytics 118

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 99

Data Lake Data Warehouse Management Risk 99

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

Alation

APRIL 14, 2022

Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. The Cloud Data Migration Challenge. Governance of Data Drift.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Alation

APRIL 6, 2023

Other forms of governance address specific sets or domains of data including information governance (for unstructured data), metadata governance (for data documentation), and domain-specific data (master, customer, product, etc.). Data catalogs and spreadsheets are related in many ways.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

AWS Big Data

JULY 28, 2023

To successfully respond to a data subject’s requests, organizations should have a clear strategy to determine how data is forgotten, flagged, anonymized, or deleted, and they should have clear guidelines in place for data audits. Data mapping involves identifying and documenting the flow of personal data in an organization.

Snapshot 80

Snapshot Metadata Measurement Data Warehouse 80

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 83

Cost-Benefit Metadata Data Governance Modeling 83

IBM Big Data Hub

MAY 9, 2023

The answer is that generative AI leverages recent advances in foundation models. Unlike traditional ML, where each new use case requires a new model to be designed and built using specific data, foundation models are trained on large amounts of unlabeled data, which can then be adapted to new scenarios and business applications.

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Proprietary file formats mean no one else is invited in!

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

Cloudera

NOVEMBER 5, 2020

When you register an Environment in CDP, a Data Lake is automatically deployed for that environment. Data Lake security and governance is managed by a shared set of services running within a Data Lake cluster. Apache Atlas — metadata management and governance: lineage, analytics, attributes.

Data Lake 70

Data Lake Data Warehouse Metadata Optimization 70

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. RDF vs LPG?

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 52

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

Cloudera

OCTOBER 7, 2022

dbt allows data teams to produce trusted data sets for reporting, ML modeling, and operational workflows using SQL, with a simple workflow that follows software engineering best practices like modularity, portability, and continuous integration/continuous development (CI/CD). Introduction.

Data Warehouse 79

Data Warehouse Data Transformation Testing Data Lake 79

AWS Big Data

JANUARY 22, 2024

Data as a product Treating data as a product entails three key components: the data itself, the metadata, and the associated code and infrastructure. In this approach, teams responsible for generating data are referred to as producers. All other teams can be data producers or data consumers.

Data-driven 85

Data-driven Advertising Metadata Data Architecture 85

Cloudera

APRIL 22, 2021

Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Businesses are also looking to move to a scale-out storage model that provides dense storages along with reliability, scalability, and performance.

Data Lake 98

Data Lake Cost-Benefit Testing Metadata 98

Cloudera

AUGUST 4, 2021

A top-notch system will include an easy-to-navigate data catalog that provides a single-pane view to administer and discover all data assets. The data is profiled and enhanced with rich metadata—including operational, social, and business context—creating trusted and reusable data assets and making them discoverable.

Data Governance 83

Data Governance Metadata Data-driven Enterprise 83

Alation

MARCH 21, 2023

When companies lack a data governance strategy , they may struggle to identify all consumer data or flag personal data as subject to compliance audits. They may also suffer from data duplication, which undermines their analytics models. Using Alation, ARC automated the data curation and cataloging process. “So

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Domino Data Lab

AUGUST 8, 2019

Across the board, organizations struggle with hiring enough data scientists. Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. then building machine learning models to recommend methods and potential collaborators to scientists. Sci Foo 2019.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Cloudera

JUNE 4, 2018

Unstructured content lacks a predefined data model; it must first undergo text extraction, classification, and enrichment to provide intelligence. the client needed an approach to: Simplify data hub ingestion, especially for large volumes of unstructured content.

Unstructured Data 45

Unstructured Data Metadata Big Data Enterprise 45

AWS Big Data

NOVEMBER 29, 2023

It enables data engineers, data scientists, and analytics engineers to define the business logic with SQL select statements and eliminates the need to write boilerplate data manipulation language (DML) and data definition language (DDL) expressions.

Data Lake 102

Data Lake Management Metrics Data Warehouse 102

Cloudera

OCTOBER 7, 2021

The need for a decentralized data mesh architecture stems from the challenges organizations faced when implementing more centralized data management architectures – challenges that can attributed to both technology (e.g., need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g.,

Metadata 122

Metadata Cost-Benefit Enterprise Interactive 122

Alation

FEBRUARY 17, 2023

For this reason, your data program will benefit from bringing data governance and data management together. Our organization is struggling with the guardrails between the data governance and management concepts. What frameworks and operating models have you seen work well? Seeing is believing!

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

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

Andrew White

MARCH 22, 2019

to weave together the governance and management of master data, application data, and less-widely shared data, and just enough enterprise metadata management. Your Future Requires You to Define Your Real Master Data. This ties into the failure of data governance and MDM (see first item in this list).

Analytics 68

Analytics Metadata Data Governance Management 68