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 89

Data Lake Data Warehouse Marketing Management 89

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 77

Metadata Data Lake Data Processing Data-driven 77

AWS Big Data

OCTOBER 3, 2023

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

Optimization 112

Optimization Snapshot Data Lake Metadata 112

AWS Big Data

DECEMBER 13, 2023

For the past 5 years, BMS has used a custom framework called Enterprise Data Lake Services (EDLS) to create ETL jobs for business users. Manually upgrading, testing, and deploying over 5,000 jobs every few quarters was time consuming, error prone, costly, and not sustainable.

Metadata 91

Metadata Data Lake Visualization Data Transformation 91

AWS Big Data

AUGUST 16, 2023

Iceberg manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Iceberg also helps guarantee data correctness under concurrent write scenarios. On the Code tab, choose Test , then Configure test event.

Data Lake 74

Data Lake Metadata Testing Snapshot 74

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

DataKitchen

OCTOBER 11, 2021

The data engineer then emails the BI Team, who refreshes a Tableau dashboard. Figure 1: Example data pipeline with manual processes. There are no automated tests , so errors frequently pass through the pipeline. Figure 2: Example data pipeline with DataOps automation. Adding Tests to Reduce Stress.

Testing 152

Testing Metadata Dashboards Statistics 152

AWS Big Data

JULY 3, 2023

Terminology Let’s first discuss some of the terminology used in this post: Research data lake on Amazon S3 – A data lake is a large, centralized repository that allows you to manage all your structured and unstructured data at any scale.

Snapshot 86

Snapshot Data Lake Testing Strategy 86

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 82

Metadata Testing Data Lake Consulting 82

AWS Big Data

JULY 20, 2023

The Hive metastore is a repository of metadata about the SQL tables, such as database names, table names, schema, serialization and deserialization information, data location, and partition details of each table. Apache Hive, Apache Spark, Presto, and Trino can all use a Hive Metastore to retrieve metadata to run queries.

Data Lake 83

Data Lake Metadata Data Processing Big Data 83

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

DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

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. Cloudera and Cisco have tested together with dense storage nodes to make this a reality. . This CVD is built using Cloudera Data Platform Private Cloud Base 7.1.5

Data Lake 100

Data Lake Cost-Benefit Testing Metadata 100

CIO Business Intelligence

NOVEMBER 4, 2022

Then the data is consumed by SaaS-based computational tools, but it still sits within our organization and sits within the controls of our cloud-based solutions.” Much of Regeneron’s data, of course, is confidential. For that reason, many of its data tools — and even its data lake — were built in-house using AWS. “We

Data Lake 103

Data Lake IT Experimentation Data-driven 103

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

NOVEMBER 29, 2023

Amazon Redshift Serverless, generally available since 2021, allows you to run and scale analytics without having to provision and manage the data warehouse. Use one click to access your data lake tables using auto-mounted AWS Glue data catalogs on Amazon Redshift for a simplified experience.

Data Warehouse 103

Data Warehouse Data Lake Analytics Machine Learning 103

AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. Let’s say that this company is located in Europe and the data product must comply with the GDPR.

Data Lake 105

Data Lake Management Metrics Data Warehouse 105

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.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 86

Data Lake Data Architecture Metadata Data Warehouse 86

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 122

Data Architecture Data Warehouse Statistics Visualization 122

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data lakehouse was created to solve these problems.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Cloudera

MARCH 17, 2023

ChatGPT is trained on historical data and depending on how one phrases their question, it may offer inaccurate or misleading information. I took the free version of ChatGPT on a test drive (in March 2023) and asked some simple questions on data lakehouse and its components.

Unstructured Data 62

Unstructured Data Data Lake Data Warehouse Machine Learning 62

Cloudera

FEBRUARY 8, 2024

The snapshotId of the source tables involved in the materialized view are also maintained in the metadata. Incremental and full rebuild of materialized view We will insert rows into the base table and examine how the materialized view can be updated to reflect the new data. Furthermore, it is partitioned on the d_year column.

Snapshot 90

Snapshot Metadata Cost-Benefit Data Warehouse 90

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 78

Metadata Data Warehouse Snapshot Data Quality 78

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 123

Metadata Visualization Data Lake Data-driven 123

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.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

AWS Big Data

NOVEMBER 17, 2023

Athena provides a simplified, flexible way to analyze petabytes of data where it lives. You can analyze data or build applications from an Amazon Simple Storage Service (Amazon S3) data lake and 30 data sources, including on-premises data sources or other cloud systems using SQL or Python.

Optimization 114

Optimization Statistics Metadata Data Lake 114

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 87

Enterprise Data Warehouse Data Lake Optimization 87

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. It consists of full-day and intraday tables.

Analytics 55

Analytics Data Lake Testing Optimization 55

Cloudera

OCTOBER 7, 2022

Using these adapters, Cloudera customers can use dbt to collaborate, test, deploy, and document their data transformation and analytic pipelines on CDP Public Cloud, CDP One, and CDP Private Cloud. 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 Testing Data Lake 81

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 137

Management Advertising Data Lake Sales 137

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 97

Management Advertising Data Lake Sales 97

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 92

Data Lake Cost-Benefit Data-driven Dashboards 92

AWS Big Data

NOVEMBER 22, 2023

Data lakes are designed for storing vast amounts of raw, unstructured, or semi-structured data at a low cost, and organizations share those datasets across multiple departments and teams. The queries on these large datasets read vast amounts of data and can perform complex join operations on multiple datasets.

Statistics 103

Statistics Data Lake Optimization Data-driven 103

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

APRIL 26, 2024

Use Lake Formation to grant permissions to users to access data. Test the solution by accessing data with a corporate identity. Audit user data access. On the Lake Formation console, choose Data lake permissions under Permissions in the navigation pane. Select Named Data Catalog resources.

Analytics 97

Analytics Data Lake Management Enterprise 97