AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 103

Data Lake Management Metrics Data Warehouse 103

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset.

Dashboards 95

Dashboards Analytics Metadata Data Warehouse 95

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 89

Data Lake Data Warehouse Data-driven B2B 89

AWS Big Data

NOVEMBER 27, 2023

Amazon Redshift , the most widely used cloud data warehouse, has evolved significantly to meet the performance requirements of the most demanding workloads. This post covers one such new feature—the multidimensional data layout sort key. Milind Oke is a Data Warehouse Specialist Solutions Architect based out of New York.

Cost-Benefit 99

Cost-Benefit Data Warehouse Optimization Testing 99

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 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

AWS Big Data

APRIL 25, 2024

As the queries finish running, an UNLOAD operation is invoked from the Redshift data warehouse to the S3 bucket in Account A. VPC endpoints are created for Amazon S3 and Secrets Manager to interact with other resources. Usually, data engineers create an Airflow Directed Acyclic Graph (DAG) and commit their changes to GitHub.

Metadata 104

Metadata Data Processing Management Testing 104

AWS Big Data

FEBRUARY 13, 2023

We live in a data-producing world, and as companies want to become data driven, there is the need to analyze more and more data. These analyses are often done using data warehouses. Status quo before migration Here at OLX Group, Amazon Redshift has been our choice for data warehouse for over 5 years.

Snapshot 67

Snapshot Data Warehouse Testing Analytics 67

erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

AWS Big Data

OCTOBER 18, 2023

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. Navigate to the side menu Virtual clusters , then select the HiveDemo cluster , You can see an entry for the SparkSQL test job.

Big Data 81

Big Data Data Processing Interactive Testing 81

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. We begin with a Data lake reference architecture followed by an overview of operational data processing framework.

Data Lake 91

Data Lake Data Processing Metadata Snapshot 91

Jet Global

FEBRUARY 23, 2024

This includes cleaning, aggregating, enriching, and restructuring data to fit the desired format. Load : Once data transformation is complete, the transformed data is loaded into the target system, such as a data warehouse, database, or another application.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

AWS Big Data

FEBRUARY 24, 2023

An AWS Glue streaming job is connected to Kinesis Data Streams to process the data using the Iceberg connector. Athena uses the AWS Glue Data Catalog to store and retrieve table metadata for the Amazon S3 data in Iceberg format. When the testing is correct, choose Send data. Choose Add database.

Data Lake 83

Data Lake Metadata Testing Data Warehouse 83

AWS Big Data

FEBRUARY 1, 2023

We also used AWS Lambda for data processing. To further optimize and improve the developer velocity for our data consumers, we added Amazon DynamoDB as a metadata store for different data sources landing in the data lake. Clients access this data store with an API’s.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

datapine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Interactive Query Synthesis from Input-Output Examples ” – Chenglong Wang, Alvin Cheung, Rastislav Bodik (2017-05-14).

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Increasingly, these were simply web servers.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

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. Supports the ability to interact with the actual data and perform analysis on it.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data. Yes—but basic dashboards won’t be enough.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

IBM Big Data Hub

JULY 17, 2023

While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases. offers a Prompt Lab, where users can interact with different prompts using prompt engineering on generative AI models for both zero-shot prompting and few-shot prompting.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Andrew White

JANUARY 11, 2021

See recorded webinars: Emerging Practices for a Data-driven Strategy. Data and Analytics Governance: Whats Broken, and What We Need To Do To Fix It. Link Data to Business Outcomes. Does Data warehouse as a software tool will play role in future of Data & Analytics strategy? Yes, and no. Policy execution.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.” Yet finding data is just the beginning.

Metadata 64

Metadata Data Governance Dashboards Software 64