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 81

Data Lake Metadata Data Processing Big Data 81

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 80

Metadata Testing Data Lake Consulting 80

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 115

Optimization Statistics Metadata Data Lake 115

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 93

Data Lake Data Processing Metadata Snapshot 93

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 56

Analytics Data Lake Testing Optimization 56

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 67

Optimization Data Lake Cost-Benefit Reporting 67

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 104

Statistics Data Lake Optimization Data-driven 104

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 86

Enterprise Data Warehouse Snapshot Cost-Benefit 86

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 116

Data Lake Metadata Optimization Statistics 116

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

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. Note the configuration parameters s3.write.tags.write-tag-name write.tags.write-tag-name and s3.delete.tags.delete-tag-name

Data Lake 85

Data Lake Snapshot Metadata Optimization 85

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). in lieu of simply landing in a data lake.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

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 87

Data Lake Data Warehouse Marketing Management 87

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 85

Snapshot Data Lake Testing Strategy 85

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

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 72

Data Lake Metadata Testing Snapshot 72

Cloudera

FEBRUARY 8, 2024

It brings the reliability and simplicity of SQL tables to big data while enabling engines like Hive, Impala, Spark, Trino, Flink, and Presto to work with the same tables at the same time. The snapshotId of the source tables involved in the materialized view are also maintained in the metadata.

Snapshot 88

Snapshot Metadata Cost-Benefit Data Warehouse 88

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

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

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 98

Data Lake Cost-Benefit Testing Metadata 98

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

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 121

Metadata Visualization Data Lake Data-driven 121

Cloudera

MAY 19, 2021

Data Ingestion. The raw data is in a series of CSV files. We will firstly convert this to parquet format as most data lakes exist as object stores full of parquet files. Parquet also stores type metadata which makes reading back and processing the files later slightly easier. Ingest Data. Write Data.

Machine Learning 136

Machine Learning Data Science Data Lake Modeling 136

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

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. The Cloud Data Migration Challenge. A useful feature for exposing patterns in the data. Visual Profiling. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

AWS Big Data

JUNE 13, 2023

Download the SAML metadata file. In the navigation pane under Clients , import the SAML metadata file. Download the Keycloak IdP SAML metadata file from that URL location. For Metadata document , upload the Keycloak IdP SAML metadata XML file you downloaded and saved to your local machine earlier. Choose Browse.

Metadata 52

Metadata Dashboards Business Intelligence Management 52

AWS Big Data

OCTOBER 2, 2023

JSON data in Amazon Redshift Amazon Redshift enables storage, processing, and analytics on JSON data through the SUPER data type, PartiQL language, materialized views, and data lake queries. After you create and test the Lambda function, you can define it as a UDF in Amazon Redshift.

Cost-Benefit 88

Cost-Benefit Metadata Structured Data Management 88

Cloudera

JUNE 6, 2019

When a mix of batch, interactive, and data serving workloads are added to the mix, the problem becomes nearly intractable. While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Cloudera Manager (CM) 6.2

Metadata 85

Metadata Data Lake Optimization Strategy 85

AWS Big Data

JUNE 12, 2023

After the processed data is stored in Amazon S3, we create an AWS Glue crawler to create a Data Catalog table that acts as a metadata layer for the data. The table can be queried using Amazon Athena , a serverless, interactive query service that enables running SQL-like queries on data stored in Amazon S3.

Management 80

Management Metadata Testing Internet of Things 80

IBM Big Data Hub

JULY 17, 2023

Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access. Easy to use, integrated data console: Bring your own data and stay in control of your data. Within the watsonx.ai

Machine Learning 66

Machine Learning Data Warehouse Modeling Cost-Benefit 66

Domino Data Lab

AUGUST 8, 2019

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 gist is, leveraging metadata about research datasets, projects, publications, etc., No big deal.”. The Big Picture.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

AWS Big Data

JUNE 19, 2023

Security Lake automatically centralizes security data from cloud, on-premises, and custom sources into a purpose-built data lake stored in your account. With Security Lake, you can get a more complete understanding of your security data across your entire organization.

Publishing 87

Publishing Dashboards Visualization Management 87

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 106

Data Lake Management Metrics Data Warehouse 106

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 92

Data Lake Data Warehouse Data-driven B2B 92

Andrew White

JANUARY 11, 2021

Does Data warehouse as a software tool will play role in future of Data & Analytics strategy? You cannot get away from a formalized delivery capability focused on regular, scheduled, structured and reasonably governed data. Data lakes don’t offer this nor should they. E.g. Data Lakes in Azure – as SaaS.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52