DataKitchen

AUGUST 9, 2021

The domain also includes code that acts upon the data, including tools, pipelines, and other artifacts that drive analytics execution. The domain requires a team that creates/updates/runs the domain, and we can’t forget metadata: catalogs, lineage, test results, processing history, etc., ….

Testing 246

Testing Data Lake Metadata Publishing 246

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Warehouse, data lake convergence. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

AWS Big Data

DECEMBER 4, 2024

In today’s data-driven world , organizations are constantly seeking efficient ways to process and analyze vast amounts of information across data lakes and warehouses. This post will showcase how this data can also be queried by other data teams using Amazon Athena. Verify that you have Python version 3.7

Data Lake 116

Data Lake Metadata Insurance Data-driven 116

IBM Big Data Hub

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

CIO Business Intelligence

MAY 24, 2022

The company said that IDMC for Financial Services has built-in metadata scanners that can help extract lineage, technical, business, operational, and usage metadata from over 50,000 systems (including data warehouses and data lakes) and applications including business intelligence, data science, CRM, and ERP software.

Finance 140

Finance Management Metadata Machine Learning 140

AWS Big Data

OCTOBER 25, 2023

But most important of all, the assumed dormant value in the unstructured data is a question mark, which can only be answered after these sophisticated techniques have been applied. Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly. The solution integrates data in three tiers.

Unstructured Data 133

Unstructured Data Metadata Management Analytics 133

Cloudera

MAY 19, 2021

This year, we expanded our partnership with NVIDIA , enabling your data teams to dramatically speed up compute processes for data engineering and data science workloads with no code changes using RAPIDS AI. Data Ingestion. The raw data is in a series of CSV files. What is RAPIDS. Register Now. .

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

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 132

Data Architecture Data Warehouse Statistics Visualization 132

CIO Business Intelligence

JUNE 9, 2022

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 144

Management Advertising Data Lake Sales 144

AWS Big Data

NOVEMBER 7, 2024

BladeBridge offers a comprehensive suite of tools that automate much of the complex conversion work, allowing organizations to quickly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse. Amazon Redshift is a fully managed data warehouse service offered by Amazon Web Services (AWS).

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

Data Virtualization

APRIL 21, 2022

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

Data Lake 59

Data Lake Data Warehouse Data Integration Management 59

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

JUNE 7, 2023

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. The target accounts read data from the source account S3 buckets.

Metadata 59

Metadata Data Lake Machine Learning Big Data 59

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

Metadata 109

Metadata Data Lake Data Processing Data-driven 109

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 Data-driven 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 94

Data Lake Data Warehouse Machine Learning Data-driven 94

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 97

Analytics Data Warehouse Data Lake Metadata 97

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 Warehouse 94

Data Warehouse Data Lake IT Analytics 94

CIO Business Intelligence

AUGUST 3, 2023

“You had to be an expert in the programming language that interacts with that data, and understand the relationships of each data element within each data source, let alone understand its relation to elements in other data sources,” he says. Without those templates, it’s hard to add such information after the fact.”

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

IBM Big Data Hub

OCTOBER 4, 2023

A data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes, to address the challenges of today’s complex data landscape and scale AI. New insights and relationships are found in this combination. All of this supports the use of AI.

Data Lake 77

Data Lake Metadata Data Warehouse Cost-Benefit 77

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Towards Data Science ). Forrester ).

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” Iceberg handles massive data born in the cloud.

Metadata 102

Metadata Machine Learning Unstructured Data Data Lake 102

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

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

CIO Business Intelligence

SEPTEMBER 22, 2023

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 105

Management Advertising Data Lake Sales 105

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale.

Management 79

Management Metadata Data Architecture Data Lake 79

Cloudera

DECEMBER 15, 2022

With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Only metadata will be regenerated. Newly generated metadata will then point to source data files as illustrated in the diagram below. . Data quality using table rollback. Metadata management .

Metadata 80

Metadata Data Warehouse Snapshot Machine Learning 80

Cloudera

JUNE 16, 2022

CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report. The DevOps/app dev team wants to know how data flows between such entities and understand the key performance metrics (KPMs) of these entities. She is a smart data analyst and former DBA working at a planet-scale manufacturing company.

Data Lake 88

Data Lake Manufacturing Metadata Dashboards 88

AWS Big Data

JULY 14, 2023

The FinAuto team built AWS Cloud Development Kit (AWS CDK), AWS CloudFormation , and API tools to maintain a metadata store that ingests from domain owner catalogs into the global catalog. This global catalog captures new or updated partitions from the data producer AWS Glue Data Catalogs.

Finance 98

Finance Metadata Big Data Recreation/Entertainment 98

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 103

Data Strategy Strategy Data Warehouse Prescriptive Analytics 103

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. Modern data (and analytics) governance does not necessarily need: Wall-to-wall discovery of your data and metadata.

Analytics 66

Analytics Data Lake Data Governance Data Warehouse 66

AWS Big Data

DECEMBER 19, 2024

The business end-users were given a tool to discover data assets produced within the mesh and seamlessly self-serve on their data sharing needs. The integration of Databricks Delta tables into Amazon DataZone is done using the AWS Glue Data Catalog. The following figure illustrates the data mesh architecture.

Data Governance 52

Data Governance Publishing Data-driven Metadata 52

Cloudera

OCTOBER 7, 2022

Cloudera’s mission, values, and culture have long centered around using open source engines on open data and table formats to enable customers to build flexible and open data lakes. To date, dbt was only available on proprietary cloud data warehouses, with very little interoperability between different engines.

Data Warehouse 81

Data Warehouse Data Transformation Machine Learning Data Lake 81

AWS Big Data

FEBRUARY 21, 2023

The data vault approach is a method and architectural framework for providing a business with data analytics services to support business intelligence, data warehousing, analytics, and data science needs. Amazon Redshift RA3 instances and Amazon Redshift Serverless are perfect choices for a data vault.

Data Warehouse 95

Data Warehouse Data Lake Cost-Benefit Metadata 95

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

MAY 9, 2023

Optimized for all data, analytics and AI workloads, watsonx.data combines the flexibility of a data lake with the performance of a data warehouse, helping businesses to scale data analytics and AI anywhere their data resides.

Data Warehouse 106

Data Warehouse Machine Learning Cost-Benefit Metadata 106

Domino Data Lab

APRIL 3, 2019

The top three items are essentially “the devil you know” for firms which want to invest in data science: data platform, integration, data prep. Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Rinse, lather, repeat.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84