AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 93

Data Governance Unstructured Data Metadata Data Lake 93

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 111

Data Lake Analytics Dashboards Metrics 111

AWS Big Data

JANUARY 24, 2024

AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. It will never remove files that are still required by a non-expired snapshot.

Snapshot 98

Snapshot Data Lake Metadata Optimization 98

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. 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

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

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

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

Cloudera

JUNE 7, 2023

The revised ZTMM is organized by five categories or pillars: identity, devices, networks, applications and workloads, and data, and four levels of maturity: traditional, initial, advanced, and optimal. It operates independently from compute and storage layers, offering integrated security and governance based on metadata.

Metadata 79

Metadata Data Lake Optimization Modeling 79

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference. Starting with Amazon EMR release 6.7.0,

Data Lake 80

Data Lake Data Governance Data Architecture Machine Learning 80

Timo Elliott

DECEMBER 14, 2022

Most innovation platforms make you rip the data out of your existing applications and move it to some another environment—a data warehouse, or data lake, or data lake house or data cloud—before you can do any innovation. The analysts call this a data mesh or data fabric strategy.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 89

Data Lake Data Processing Metadata Snapshot 89

CIO Business Intelligence

DECEMBER 4, 2023

Beyond “records,” organizations can digitally capture anything and apply metadata for context and searchability. For example, a purpose-built content services platform and well-architected data lake can provide easy access for automation and AI use. Structure/Operationalize. Artificial Intelligence

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

AWS Big Data

AUGUST 31, 2023

Amazon Redshift enables you to directly access data stored in Amazon Simple Storage Service (Amazon S3) using SQL queries and join data across your data warehouse and data lake. With Amazon Redshift, you can query the data in your S3 data lake using a central AWS Glue metastore from your Redshift data warehouse.

Data Lake 91

Data Lake Data Warehouse Metadata Data Architecture 91

Ontotext

NOVEMBER 16, 2023

Data mesh is still in its infancy, and data personas and organizations are craving clarity and specificity. It is critical to be aware of the “why” and “what” and fully understand the role that knowledge graphs play when considering adopting a data mesh strategy. The debate on what constitutes a data mesh rages on.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

AWS Big Data

DECEMBER 5, 2023

A combination of Amazon Redshift Spectrum and COPY commands are used to ingest the survey data stored as CSV files. For the files with unknown structures, AWS Glue crawlers are used to extract metadata and create table definitions in the Data Catalog. The first image shows the dashboard without any active filters.

Measurement 81

Measurement Dashboards Data Warehouse Analytics 81

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. Integrating data across this hybrid ecosystem can be time consuming and expensive. The volume of data assets.

Data-driven 57

Data-driven Enterprise Data Governance Data Lake 57

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.

Data Governance 145

Data Governance IT Risk Data Lake 145

Alation

APRIL 18, 2023

Gartner defines data profiling as: A technology for discovering and investigating data quality issues, such as duplication, lack of consistency, and lack of accuracy and completeness. The tools provide data statistics, such as degree of duplication and ratios of attribute values, both in tabular and graphical formats.

IT 52

IT Data Quality Metadata Data Governance 52

AWS Big Data

APRIL 25, 2024

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

Optimization 65

Optimization Data Lake Cost-Benefit Reporting 65

bridgei2i

MARCH 11, 2021

How Can Small Businesses Benefit from an AI Data Company? We all know how Artificial Intelligence helps giants like Google and Amazon reshape their commercial techniques and business strategies. Easily understandable, highly curated, and reliable data helps Machine Learning (ML) tools evolve. What is a Data Governance Strategy?

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

Octopai

MAY 30, 2019

If the point of Business Intelligence (BI) data governance is to leverage your datasets to support information transparency and decision-making, then it’s fair to say that the data catalog is key for your BI strategy. At least, as far as data analysis is concerned. Folding In Metadata Automation. Scalability.

Metadata 40

Metadata Data Governance Data Lake IoT 40

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. Creating a High-Quality Data Pipeline.

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 111

Data Lake Metadata Optimization Statistics 111

Andrew White

OCTOBER 22, 2021

Monetization/Link data to outcome (value pyramid) business value of data/business impact 20. D&A Strategy/infusing business with (overall) 16. Business Information Model/Arch compared to classic enterprise data model and how to relate it to catalogs and marketplaces and enterprise data models 13.

IT 52

IT Data Lake Strategy Data Science 52

CIO Business Intelligence

SEPTEMBER 6, 2022

Very has come full circle as a business built on catalog data, but it took some introspection in order to figure out the best way to get there. Understanding what data you’ve got locked in all these different stores is a big part of the jigsaw puzzle.”.

IT 89

IT Forecasting Data Lake Enterprise 89

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. availability. You still need to set appropriate EMRFS retries to provide additional resiliency.

Data Lake 83

Data Lake Snapshot Metadata Optimization 83

Alation

JANUARY 26, 2023

Data is a key asset for businesses in the modern world. Used correctly, it can improve internal operations, power marketing strategies, and much more. That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. This is why data also needs to be compliant.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

TDAN

MARCH 19, 2019

Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years. The emergence of various new concepts, technologies, and applications such as Hadoop, Tableau, R, Power BI, or Data Lakes indicate that changes are under way.

Management 84

Management Data Lake Data Warehouse Analytics 84

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: workload analysis and replication, migrating or bursting to cloud, data warehouse optimization, and more. DATA FOR GOOD. Enterprise Data Cloud: West Midlands Police — WMP public cloud data platform allows fast data insights and positive community interventions .

Digital Transformation 66

Digital Transformation Machine Learning Optimization Data Lake 66

Cloudera

AUGUST 21, 2020

To start off, what are the advantages of a forward-looking data-in-motion strategy? Data-in-motion is predominantly about streaming data so enterprises typically have two different ways or binary ways of looking at data. Hi Dinesh, thank you for joining us for today’s Q&A.

Enterprise 59

Enterprise Data Lake Strategy Metadata 59

AWS Big Data

JULY 21, 2023

Data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts.

Data Lake 85

Data Lake Data Warehouse Marketing Management 85

AWS Big Data

JANUARY 8, 2024

Stream Processing – An application created with Amazon Managed Service for Apache Flink can read the records from the data stream to detect and clean any errors in the time series data and enrich the data with specific metadata to optimize operational analytics.

Analytics 111

Analytics IoT Data-driven Snapshot 111

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 86

Data Lake Analytics Snapshot Optimization 86

Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

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