AWS Big Data

APRIL 19, 2023

We split the solution into two primary components: generating Spark job metadata and running the SQL on Amazon EMR. The first component (metadata setup) consumes existing Hive job configurations and generates metadata such as number of parameters, number of actions (steps), and file formats. sql_path SQL file name.

Metadata 76

Metadata Testing Data Lake Consulting 76

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

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

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

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

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

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 65

Digital Transformation Machine Learning Optimization Data Lake 65

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

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 109

Analytics IoT Data-driven Snapshot 109

AWS Big Data

JANUARY 24, 2023

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. This solution only replicates metadata in the Data Catalog, not the actual underlying data.

Data Architecture 64

Data Architecture Metadata Data Lake Snapshot 64

AWS Big Data

OCTOBER 4, 2023

An Amazon DataZone domain contains an associated business data catalog for search and discovery, a set of metadata definitions to decorate the data assets that are used for discovery purposes, and data projects with integrated analytics and ML tools for users and groups to consume and publish data assets.

Metadata 96

Metadata Data Lake Publishing Data Governance 96

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

IBM Big Data Hub

OCTOBER 4, 2023

Artificial intelligence (AI) is now at the forefront of how enterprises work with data to help reinvent operations, improve customer experiences, and maintain a competitive advantage. It’s no longer a nice-to-have, but an integral part of a successful data strategy. from 2022 to 2026. All of this supports the use of AI.

Data Lake 86

Data Lake Metadata Cost-Benefit Data Warehouse 86

AWS Big Data

OCTOBER 25, 2023

Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Alation

JULY 7, 2022

With Alation, students learn the critical skills they need to curate, govern, and discover data assets in the data-driven enterprises of today. Two data-driven careers. In 2013 I joined American Family Insurance as a metadata analyst. For the uninitiated, metadata is “data about data” – and it’s everywhere.

Metadata 52

Metadata Data-driven Insurance Statistics 52

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 89

Management Metadata Data Architecture Data Lake 89

AWS Big Data

APRIL 26, 2024

In this post, we show how to bring your workforce identity to EMR Studio for analytics use cases, directly manage fine-grained permissions for the corporate users and groups using Lake Formation, and audit their data access. Both enterprise users from Okta are provisioned in IAM Identity Center. Choose Create.

Analytics 81

Analytics Data Lake Management Enterprise 81

AWS Big Data

DECEMBER 18, 2023

Solution overview One of the common functionalities involved in data pipelines is extracting data from multiple data sources and exporting it to a data lake or synchronizing the data to another database. There are multiple tables related to customers and order data in the RDS database.

Metadata 117

Metadata Visualization Data Lake Data-driven 117

AWS Big Data

MARCH 26, 2024

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. Let’s find out what role each of these components play in the context of C360.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Cloudera

AUGUST 4, 2021

Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. As a result, it’s easier to find people to handle highly routine-oriented data governance positions. Security: It must serve data throughout a system.

Data Governance 82

Data Governance Metadata Data-driven Enterprise 82

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

Cloudera

DECEMBER 16, 2022

This validates our significant momentum in global enterprises. We’re proud to be recognized for the data management and data analytics innovations we have delivered in the new Cloudera Data Platform (CDP). Only Cloudera delivers the hybrid and multi-cloud flexibility enterprises need today.

Management 88

Management Metadata Machine Learning Data Lake 88

AWS Big Data

FEBRUARY 21, 2023

Because data is closer to the source and stored in raw format, it has to be transformed before it can be used for reporting and other application purposes. This is one of the biggest hurdles with the data vault approach. It is a data modeling methodology designed for large-scale data warehouse platforms.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

IBM Big Data Hub

MAY 9, 2023

Today we have one of the most comprehensive portfolios of enterprise AI solutions available. It makes our supply chains stronger, defends critical enterprise data against cyber attackers, and helps deliver seamless experiences to millions of customers ever day across multiple industries. Watsonx.ai

Data Warehouse 108

Data Warehouse Cost-Benefit Machine Learning Modeling 108

Alation

APRIL 14, 2022

Moving data to the cloud can bring immense operational benefits. However, the sheer volume and complexity of today’s enterprise data can cause downstream headaches for data users. Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. 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. Metadata in cluster is disjoint across components.

Data Lake 98

Data Lake Cost-Benefit Testing Metadata 98

IBM Big Data Hub

OCTOBER 12, 2023

Ensuring compliance with governmental regulatory requirements as well as internal policies An AI model must be fully understood from every angle, inside and out—from what enterprise data is used and when , to how the model arrived at a certain output. Learn more about IBM watsonx 1.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Alation

JULY 19, 2022

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. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses. Let’s summarize very quickly.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Cloudera

AUGUST 21, 2020

Over time, additional use cases and functions expanded from original EDW and Data Lake related functions to support increasing demands from the business. More sources, data, and functionality were added to these platforms, expanding their value but adding to the complexity, such as: Streaming data ingestion. .

Cost-Benefit 71

Cost-Benefit Big Data ROI Risk 71

Cloudera

JANUARY 22, 2019

In conjunction with the evolving data ecosystem are demands by business for reliable, trustworthy, up-to-date data to enable real-time actionable insights. Big Data Fabric has emerged in response to modern data ecosystem challenges facing today’s enterprises. What is Big Data Fabric?

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Domino Data Lab

AUGUST 8, 2019

There’s been a flurry of tech startups, open source frameworks, enterprise products, etc., I mention this here because there was a lot of overlap between current industry data governance needs and what the scientific community is working toward for scholarly infrastructure. The real fun begins once models get deployed in production.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Cloudera

JUNE 16, 2022

Every large enterprise organization is attempting to accelerate their digital transformation strategies to engage with their customers in a more personalized, relevant, and dynamic way. The ability to perform analytics on data as it is created and collected (a.k.a. What is Kafka blindness? Who is affected?

Data Lake 83

Data Lake Manufacturing Metadata Dashboards 83

CIO Business Intelligence

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices.

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. by building data products with domain owners.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

Andrew White

JANUARY 11, 2021

What is your vision for D&A for small and medium enterprises? We have specific research for midsize and small enterprises. See 3 Questions That Midsize Enterprises Should Ask About Data and Analytics and have an inquiry with Alan Duncan. Which industry, sector moves fast and successful with data-driven?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52