AWS Big Data

MARCH 25, 2024

With a few clicks, MSK Connect allows you to deploy connectors that move data between Apache Kafka and external systems. MSK Connect now supports the ability to delete MSK Connect worker configurations, tag resources, and manage worker configurations and custom plugins using AWS CloudFormation. Provide a name and optional description.

Management 114

Management Metadata Reporting Big Data 114

AWS Big Data

JULY 3, 2023

Backtesting is a process used in quantitative finance to evaluate trading strategies using historical data. We specifically explore how Amazon EMR and the newly developed Apache Iceberg branching and tagging feature can address the challenge of look-ahead bias in backtesting.

Snapshot 105

Snapshot Data Lake Testing Strategy 105

DataKitchen

OCTOBER 28, 2021

We have the tools to create data analytics workflows that address AI bias. When our work processes for creating and monitoring analytics contain built-in controls against bias, data analytics organizations will no longer be dependent on individual social awareness or heroism. What Is AI Bias? What Is AI Bias?

Testing 130

Testing IT Manufacturing Machine Learning 130

AWS Big Data

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data. Query the data using Athena.

Snapshot 132

Snapshot Data Lake Metadata Recreation/Entertainment 132

AWS Big Data

JULY 25, 2024

AWS Data Pipeline helps customers automate the movement and transformation of data. With Data Pipeline, customers can define data-driven workflows, so that tasks can be dependent on the successful completion of previous tasks. The option you choose depends on your current workload on Data Pipeline.

Visualization 115

Visualization Management Data Integration Testing 115

AWS Big Data

JULY 26, 2023

Data is a key enabler for your business. Many AWS customers have integrated their data across multiple data sources using AWS Glue , a serverless data integration service, in order to make data-driven business decisions. Are there recommended approaches to provisioning components for data integration?

Data Integration 97

Data Integration Snapshot Testing Visualization 97

AWS Big Data

NOVEMBER 17, 2023

Amazon Redshift is a cloud data warehousing service that provides high-performance analytical processing based on a massively parallel processing (MPP) architecture. Building and maintaining data pipelines is a common challenge for all enterprises. Macros – These are pieces of code that can be reused multiple times.

Snapshot 111

Snapshot Data Processing Testing Data Warehouse 111

DataKitchen

JUNE 24, 2021

In May 2021 at the CDO & Data Leaders Global Summit, DataKitchen sat down with the following data leaders to learn how to use DataOps to drive agility and business value. Kurt Zimmer, Head of Data Engineering for Data Enablement at AstraZeneca. Jim Tyo, Chief Data Officer, Invesco. Data takes a long journey.

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

IBM Big Data Hub

NOVEMBER 29, 2023

In this paper, we showcase how to easily deploy a banking application on both IBM Cloud for Financial Services and Satellite , using automated CI/CD/CC pipelines in a common and consistent manner. To achieve the deployment on Satellite the CI/CC pipelines were reused, and a new CD pipeline was created.

Testing 89

Testing Dashboards Risk Data Processing 89

IBM Big Data Hub

MARCH 25, 2022

To simplify data access and empower users to leverage trusted information, organizations need a better approach that provides better insights and business outcomes faster, without sacrificing data access controls. There are many different approaches, but you’ll want an architecture that can be used regardless of your data estate.

Metadata 104

Metadata Data Quality Data Governance Data Integration 104

Cloudera

SEPTEMBER 28, 2020

Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. Data Science and machine learning workloads using CDSW.

Testing 132

Testing Metadata Risk Data Science 132

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

Cloudera

JUNE 26, 2023

Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster. For data engineering and data science teams, CDSW is highly effective as a comprehensive platform that trains, develops, and deploys machine learning models.

Data Processing 76

Data Processing Testing Visualization Data Science 76

AWS Big Data

MAY 31, 2024

This encompasses tasks such as integrating diverse data from various sources with distinct formats and structures, optimizing the user experience for performance and security, providing multilingual support, and optimizing for cost, operations, and reliability.

Metadata 135

Metadata Data-driven Management Testing 135

AWS Big Data

APRIL 25, 2024

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a managed orchestration service for Apache Airflow that you can use to set up and operate data pipelines in the cloud at scale. The data engineering team wants to separate the raw data into its own AWS account (Account B in the diagram) for increased security and control.

Metadata 132

Metadata Data Processing Management Testing 132

AWS Big Data

MAY 23, 2024

With in-place version upgrades, upgrading your application runtime version can be achieved simply, statefully, and without incurring data loss or adding additional orchestration to your workload. In addition, logs, metrics, application tags, application configurations, VPCs, and other settings are retained between version upgrades.

Snapshot 115

Snapshot Management Testing Consulting 115

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. Picture a scenario where you, the VP of Data and Analytics, are in charge of your data and analytics environments and workloads running on AWS where you manage a team of data engineers and analysts.

Reporting 96

Reporting Metrics Optimization Data Lake 96

AWS Big Data

MAY 9, 2024

As data analytics use cases grow, factors of scalability and concurrency become crucial for businesses. Your analytic solution architecture should be able to handle large data volumes at high concurrency and without compromising speed, thereby delivering a scalable high-performance analytics environment. Enter the endpoint name.

Testing 105

Testing Cost-Benefit Reporting Optimization 105

Domino Data Lab

MAY 1, 2019

This Domino Data Science Field Note provides highlights and excerpted slides from Chloe Mawer ’s “ The Ingredients of a Reproducible Machine Learning Model ” talk at a recent WiMLDS meetup. Mawer is a Principal Data Scientist at Lineage Logistics as well as an Adjunct Lecturer at Northwestern University. Introduction.

Machine Learning 81

Machine Learning Testing Data Science Modeling 81

CIO Business Intelligence

APRIL 15, 2024

Proceeding with caution While H&R Block’s leadership and board were enticed by the possibilities of gen AI, Lowden notes he had to address some concerns before they fully bought into the project, especially with regard to safety and data privacy. “No The first was safety and data privacy testing. The third was guardrails.

Testing 102

Testing Machine Learning Data Quality Experimentation 102

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. Quite simply, metadata is data about data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

IBM Big Data Hub

DECEMBER 19, 2023

Stage 1: Development automation Infrastructure automation (IaC) and pipeline automation are self-contained within the development team, which makes automation a great place to start. Build AuthN/AuthZ integration patterns that abstract nuances and standardize authentication and authorization of applications, data and services.

Testing 74

Testing Enterprise Modeling Software 74

AWS Big Data

JULY 18, 2024

Over the years, organizations have invested in creating purpose-built, cloud-based data lakes that are siloed from one another. A major challenge is enabling cross-organization discovery and access to data across these multiple data lakes, each built on different technology stacks.

Data Lake 130

Data Lake Publishing Metadata Data-driven 130

AWS Big Data

OCTOBER 4, 2023

Amazon EMR provides a managed Hadoop framework that makes it straightforward, fast, and cost-effective to process vast amounts of data using EC2 instances. Amazon EMR with Spot Instances allows you to reduce costs for running your big data workloads on AWS. The following diagram illustrates this architecture.

Big Data 114

Big Data Optimization Data-driven Management 114

Wayne Yaddow

MARCH 14, 2025

How dbt Core aids data teams test, validate, and monitor complex data transformations and conversions Photo by NASA on Unsplash Introduction dbt Core, an open-source framework for developing, testing, and documenting SQL-based data transformations, has become a must-have tool for modern data teams as the complexity of data pipelines grows.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

IBM Big Data Hub

MARCH 22, 2024

However, various challenges arise in the QA domain that affect test case inventory, test case automation and defect volume. Managing test case inventory can become problematic due to the sheer volume of cases, which lead to inefficiencies and resource constraints.

Testing 74

Testing Optimization Software Risk 74

AWS Big Data

OCTOBER 5, 2023

Customers face a challenge when distributing cloud resources between different teams running workloads such as development, testing, or production. In this post, we show how to define per-team resource limits for big data workloads using EMR serverless. and you need to test the same workload on Amazon EMR 6.10.0,

Big Data 64

Big Data Cost-Benefit Testing Dashboards 64

AWS Big Data

MAY 3, 2023

In this post, we walk through creating a new PySpark project that analyzes weather data from the NOAA Global Surface Summary of Day open dataset. to run and is tested on macOS, Linux, and Windows. One use case for this is with CI/CD pipelines. Most CI/CD pipelines allow you to access the git tag.

Data Processing 110

Data Processing Management Testing IT 110

AWS Big Data

APRIL 3, 2024

Today, we are pleased to announce that Amazon DataZone is now able to present data quality information for data assets. Other organizations monitor the quality of their data through third-party solutions. Amazon DataZone now integrates directly with AWS Glue to display data quality scores for AWS Glue Data Catalog assets.

Data Quality 119

Data Quality Visualization Metadata Metrics 119

AWS Big Data

MARCH 11, 2024

In this post, you can learn about the Managed Service for Apache Flink cost model, areas to save on cost in your Apache Flink applications, and overall gain a better understanding of your data processing pipelines. An additional KPU per application is also charged for orchestration and not directly used for data processing.

Management 126

Management Snapshot Metrics Cost-Benefit 126

Domino Data Lab

OCTOBER 14, 2020

Guest post by Jeff Melching, Distinguished Engineer / Chief Architect Data & Analytics. We’ve developed a model-driven software platform, called Climate FieldView , that captures, visualizes, and analyzes a vast array of data for farmers and provides new insight and personalized recommendations to maximize crop yield.

Experimentation 99

Experimentation Deep Learning Modeling Testing 99

AWS Big Data

JUNE 6, 2023

As most organizations, that have turned to Google Analytics (GA) as a digital analytics solution, mature they discover a more pressing need to integrate this data silo with the rest of their organization’s data to enable better analytics and resulting product development and fraud detection.

Analytics 59

Analytics Data Lake Testing Optimization 59

Cloudera

JUNE 28, 2022

In a previous blog of this series, Turning Streams Into Data Products , we talked about the increased need for reducing the latency between data generation/ingestion and producing analytical results and insights from this data. containing data that may have to be used to enrich the streaming data.

Dashboards 85

Dashboards Machine Learning Statistics KPI 85

IBM Big Data Hub

DECEMBER 19, 2023

Rapidly deploying applications to cloud requires not just development acceleration with continuous integration, deployment and testing (CI/CD/CT), It also requires supply chain lifecycle acceleration, which involves multiple other groups such as governance risk and compliance (GRC), change management, operations, resiliency and reliability.

Data-driven 64

Data-driven Enterprise Software Testing 64

DataRobot Blog

JUNE 16, 2022

Airflow is a perfect tool to orchestrate stages of the DataRobot machine learning (ML) pipeline, because it provides an easy but powerful solution to integrate DataRobot capabilities into bigger pipelines, combine it with other services, as well as to clean your data, and store or publish the results. DataRobot Provider Modules.

Machine Learning 59

Machine Learning Modeling Testing Publishing 59

bridgei2i

MARCH 3, 2021

Episode 4: Unlocking the Value of Enterprise AI with Data Engineering Capabilities. Unlocking the Value of Enterprise AI with Data Engineering Capabilities. They discuss how the data engineering team is instrumental in easing collaboration between analysts, data scientists and ML engineers to build enterprise AI solutions.

Enterprise 98

Enterprise Digital Transformation Data-driven Interactive 98

Cloudera

JANUARY 30, 2019

It’s official – Cloudera and Hortonworks have merged , and today I’m excited to announce the availability of Cloudera Data Science Workbench (CDSW) for Hortonworks Data Platform (HDP). Trusted by large data science teams across hundreds of enterprises —. Sound familiar? What is CDSW? Install any library or framework (e.g.

Data Science 76

Data Science Machine Learning Experimentation Visualization 76