AWS Big Data

JANUARY 27, 2023

The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep track of data in data silos. Apache Flink is a widely used data processing engine for scalable streaming ETL, analytics, and event-driven applications. Apache Hudi also has its own catalog management.

Data Lake 63

Data Lake Metadata Business Analysis Data-driven 63

AWS Big Data

APRIL 11, 2023

Inventory management is a critical function for any business that deals with physical products. The primary challenge businesses face with inventory management is balancing the cost of holding inventory with the need to ensure that products are available when customers demand them.

Forecasting 78

Forecasting Management IoT Data-driven 78

AWS Big Data

APRIL 30, 2024

Amazon Q Developer can now generate complex data integration jobs with multiple sources, destinations, and data transformations. Generated jobs can use a variety of data transformations, including filter, project, union, join, and custom user-supplied SQL. Matt Su is a Senior Product Manager on the AWS Glue team.

Data Integration 104

Data Integration Data Lake Data Warehouse Software 104

AWS Big Data

DECEMBER 13, 2023

In collaboration with AWS, BMS identified a business need to migrate and modernize their custom extract, transform, and load (ETL) platform to a native AWS solution to reduce complexities, resources, and investment to upgrade when new Spark, Python, or AWS Glue versions are released.

Metadata 90

Metadata Data Lake Visualization Data Transformation 90

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 95

Data Lake Snapshot Big Data Data-driven 95

IBM Big Data Hub

OCTOBER 16, 2023

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. It can be used with both on-premise and multi-cloud environments.

Risk 72

Risk Modeling Management Metadata 72

DataKitchen

JULY 27, 2023

Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. It provides data prep, management, and enterprise data warehousing tools. It has a data pipeline tool , as well. It does the job.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

CIO Business Intelligence

JUNE 29, 2022

Analytics is the means for discovering those insights, and doing it well requires the right tools for ingesting and preparing data, enriching and tagging it, building and sharing reports, and managing and protecting your data and insights. Azure Data Factory. Azure Data Lake Analytics.

Data Lake 104

Data Lake Analytics Data Warehouse Machine Learning 104

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 94

Data Warehouse Data Lake Analytics Data Science 94

CIO Business Intelligence

AUGUST 3, 2023

It also helps him democratize credit union data so it can be used to improve customer service, automate the maintenance of such data by making various types of data easier to find, and provide chains of custody and audit controls to help meet regulatory needs.

Analytics 84

Analytics Data Lake Metadata Cost-Benefit 84

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 91

Data Lake Data Warehouse Data-driven B2B 91

CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America.

Unstructured Data 97

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 97

Ontotext

FEBRUARY 12, 2024

This promotes data autonomy and enables decision-making about data domains without centralized gatekeepers. It also breaks down the code and data monolith and distributes it across the domain teams, which results in better management and scalability. However, data mesh is not about introducing new technologies.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

APRIL 26, 2023

Additionally, this forecasting system needs to provide data enrichment steps including byproducts, serve as the master data around the semiconductor management, and enable further use cases at the BMW Group. To enable this use case, we used the BMW Group’s cloud-native data platform called the Cloud Data Hub.

Forecasting 124

Forecasting Manufacturing Data Lake Big Data 124

Cloudera

NOVEMBER 29, 2021

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . The company needed a modern data architecture to manage the growing traffic effectively. .

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

AWS Big Data

MAY 9, 2023

AWS Glue manages running Spark and adjusts workers to achieve the best price performance. For workloads such as data transforms, joins, and queries, you can use G.1X Example: Memory-intensive transformations Data transformations are an essential step to preprocess and structure your data into an optimal form.

Data Lake 90

Data Lake Cost-Benefit Data Integration Data Transformation 90

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. Solution overview The new native OpenSearch Service connector is a powerful tool that can help organizations unlock the full potential of their data.

Analytics 98

Analytics IT Data Lake Visualization 98

IBM Big Data Hub

JUNE 15, 2023

It is comprised of commodity cloud object storage, open data and open table formats, and high-performance open-source query engines. To help organizations scale AI workloads, we recently announced IBM watsonx.data , a data store built on an open data lakehouse architecture and part of the watsonx AI and data platform.

Data Warehouse 88

Data Warehouse Data Lake Optimization Data-driven 88

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 86

Data Lake Data Architecture Metadata Data Warehouse 86

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: A mostly new platform.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Cloudera

OCTOBER 11, 2021

Modak Nabu reliably curates datasets for any line of business and personas, from business analysts to data scientists. Customers using Modak Nabu with CDP today have deployed Data Lakes and. Figure 1: CDE containerized service for operational management of spark workloads. Integrated security model .

Data Lake 92

Data Lake Cost-Benefit Data-driven Dashboards 92

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. The Open Data Lakehouse . This variety can result in a lack of standardization, leading to data duplication and inconsistency.

Data Warehouse 81

Data Warehouse Data Transformation Testing Data Lake 81

AWS Big Data

NOVEMBER 9, 2023

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. This separation further simplifies data management and enhances the system’s overall performance.

Data Warehouse 106

Data Warehouse Testing Data Quality Reporting 106

AWS Big Data

NOVEMBER 7, 2023

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation. They used Amazon Aurora MySQL zero-ETL integration with Amazon Redshift to achieve this.

Dashboards 73

Dashboards Data-driven Data Integration Data Lake 73

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 Data Lake Optimization 86

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

O'Reilly on Data

OCTOBER 19, 2021

Since software engineers manage to build ordinary software without experiencing as much pain as their counterparts in the ML department, it begs the question: should we just start treating ML projects as software engineering projects as usual, maybe educating ML practitioners about the existing best practices? Orchestration. Versioning.

IT 342

IT Testing Experimentation Software 342

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 77

Cost-Benefit Metadata Optimization Management 77

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 65

Optimization Data Lake Cost-Benefit Reporting 65

Cloudera

OCTOBER 13, 2020

CDP Data Hub: a VM/Instance-based service that allows IT and developers to build custom business applications for a diverse set of use cases with secure, self-service access to enterprise data. . Enrich – Data Engineering (Apache Spark and Apache Hive). Predict – Data Engineering (Apache Spark). This is Now.

Data Warehouse 94

Data Warehouse Machine Learning Visualization Data Lake 94

AWS Big Data

MARCH 3, 2023

In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

MARCH 3, 2023

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes.

Data Lake 85

Data Lake Dashboards Metrics Metadata 85

AWS Big Data

FEBRUARY 6, 2023

Refactoring coupled compute and storage to a decoupling architecture is a modern data solution. It enables compute such as EMR instances and storage such as Amazon Simple Storage Service (Amazon S3) data lakes to scale. The tool supports HTTPS protocol to communicate with YARN Resource Manager.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

CIO Business Intelligence

OCTOBER 11, 2022

This initiative alone has generated an explosion in the quantity and complexity of data the company collects, stores, and analyzes for insights. . “We Four ways to improve data-driven business transformation . Gurinder Kaur, Vice President of Operations IT, AstraZeneca AstraZeneca. Start small, think big, and scale fast. “You

Machine Learning 144

Machine Learning Data-driven Testing Data Science 144

AWS Big Data

DECEMBER 5, 2023

For files with known structures, a Redshift stored procedure is used, which takes the file location and table name as parameters and runs a COPY command to load the raw data into corresponding Redshift tables. Finally, the dashboard’s user-friendly interface made survey data more accessible to a wider range of stakeholders.

Measurement 84

Measurement Dashboards Data Warehouse Analytics 84