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 80

Enterprise Data Warehouse Snapshot Cost-Benefit 80

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. What was at first a data stream has morphed into a data river as enterprise businesses are harvesting reams of data from every conceivable input across every conceivable business function.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

erwin

SEPTEMBER 3, 2020

Why should you integrate data governance (DG) and enterprise architecture (EA)? Two of the biggest challenges in creating a successful enterprise architecture initiative are: collecting accurate information on application ecosystems and maintaining the information as application ecosystems change.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 98

Data Lake Data Warehouse Machine Learning Cost-Benefit 98

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 91

Data Lake Data Warehouse Machine Learning Cost-Benefit 91

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. Another complication was the existing data silos.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

CIO Business Intelligence

MAY 24, 2022

Just after launching a focused data management platform for retail customers in March, enterprise data management vendor Informatica has now released two more industry-specific versions of its Intelligent Data Management Cloud (IDMC) — one for financial services, and the other for health and life sciences.

Finance 140

Finance Management Metadata Data Quality 140

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 109

Data Lake Analytics Dashboards Metrics 109

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. By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage.

Data-driven 59

Data-driven Enterprise Data Governance Data Lake 59

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

Alation

FEBRUARY 13, 2020

In an earlier blog, I defined a data catalog as “a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses.”.

Metadata 52

Metadata Management Data Lake Data Governance 52

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 89

Data Lake Snapshot Big Data Data-driven 89

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data.

Risk 78

Risk Modeling Management Metadata 78

erwin

OCTOBER 31, 2019

Data security incidents may be the result of not having a true data governance foundation that makes it possible to understand the context of data – what assets exist and where, the relationship between them and enterprise systems and processes, and how and by what authorized parties data is used. No Hocus Pocus.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

Timo Elliott

DECEMBER 14, 2022

Gartner calls it the Composable Enterprise , for example – it’s about having a solid information foundation that enables fast and flexible creation of what they call composable applications that allow you to create new applications and workflows by just bringing together modular components. Business Process.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. We split the solution into two primary components: generating Spark job metadata and running the SQL on Amazon EMR. The script generates a metadata JSON file for each step.

Metadata 76

Metadata Testing Data Lake Consulting 76

Alation

FEBRUARY 13, 2020

Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. When speaking and consulting, I often hear people refer to data in their data lakes and data warehouses as curated data, believing that it is curated because it is stored as shareable data.

Metadata 52

Metadata Data Warehouse Data Lake Data Governance 52

IBM Big Data Hub

JANUARY 5, 2023

Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues. Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Timo Elliott

JUNE 19, 2023

So analysts like Gartner talk about the composable enterprise, where we can create new end-to-end business workflows in a more modular, agile, and flexible way simply by putting together LEGO bricks, if you like, to create end-to-end workflows and processes. The next area is data. There’s a huge disruption around data.

Data Lake 105

Data Lake Digital Transformation Recreation/Entertainment Technology 105

Ontotext

NOVEMBER 16, 2023

Clarifying what data mesh is and how it works is important, but even more so is starting with the why. Why Organizations Need A Data Mesh The data mesh paradigm aims to address some of the biggest pain points for most organizations. This becomes particularly problematic when dealing with veracity of data.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Andrew White

DECEMBER 9, 2019

The client had recently engaged with a well-known consulting company that had recommended a large data catalog effort to collect all enterprise metadata to help identify all data and business issues. With this, the recommendation was the formation of a large enterprise data governance board with CEO sponsorship.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

Ontotext

MARCH 8, 2023

Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Each team and system need to keep diverse sets of data about their customers in order to play their specific role – inadvertently leading to siloed experiences. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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

erwin

APRIL 2, 2021

With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Do You Know Where Your Sensitive Data Is?

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

AWS Big Data

MARCH 25, 2024

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. With a file system sink connector, Apache Flink jobs can deliver data to Amazon S3 in open format (such as JSON, Avro, Parquet, and more) files as data objects.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

CIO Business Intelligence

SEPTEMBER 6, 2022

When Steve Pimblett joined The Very Group in October 2020 as chief data officer, reporting to the conglomerate’s CIO, his task was to help the enterprise uncover value in its rich data heritage. As a result, Pimblett now runs the organization’s data warehouse, analytics, and business intelligence.

IT 98

IT Forecasting Data Lake Enterprise 98

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

AWS Big Data

MARCH 29, 2024

Data Firehose uses an AWS Lambda function to transform data and ingest the transformed records into an Amazon Simple Storage Service (Amazon S3) bucket. An AWS Glue crawler scans data on the S3 bucket and populates table metadata on the AWS Glue Data Catalog.

Metrics 101

Metrics Visualization Dashboards Interactive 101

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. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

Data Lake 87

Data Lake Data Processing Metadata Snapshot 87

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

Data Virtualization

MARCH 3, 2021

To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is. The post Data Management Challenges for the Modern Enterprise appeared first on Data Virtualization blog.

Enterprise 75

Enterprise Management Strategy Data Lake 75

Alation

FEBRUARY 13, 2020

Why do we need a data catalog? What does a data catalog do? These are all good questions and a logical place to start your data cataloging journey. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. Figure 1 – Data Catalog Metadata Subjects.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Cloudera

NOVEMBER 12, 2020

Your sunk costs are minimal and if a workload or project you are supporting becomes irrelevant, you can quickly spin down your cloud data warehouses and not be “stuck” with unused infrastructure. Cloud deployments for suitable workloads gives you the agility to keep pace with rapidly changing business and data needs.

Data Warehouse 102

Data Warehouse Reporting Risk Cost-Benefit 102

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. SECURITY AND GOVERNANCE LEADERSHIP.

Digital Transformation 67

Digital Transformation Machine Learning Optimization Data Lake 67

Andrew White

OCTOBER 22, 2021

Monetization/Link data to outcome (value pyramid) business value of data/business impact 20. Business Information Model/Arch compared to classic enterprise data model and how to relate it to catalogs and marketplaces and enterprise data models 13. Lakehouse (data warehouse and data lake working together) 8.

IT 52

IT Data Lake Strategy Data Science 52