AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 94

Metadata Data Lake Visualization Data Quality 94

AWS Big Data

AUGUST 9, 2024

These processes retrieve data from around 90 different data sources, resulting in updating roughly 2,000 tables in the data warehouse and 3,000 external tables in Parquet format, accessed through Amazon Redshift Spectrum and a data lake on Amazon Simple Storage Service (Amazon S3). We started with 115 dc2.large

Data Lake 101

Data Lake Analytics Data Warehouse Data-driven 101

DataKitchen

JULY 27, 2023

Here are a few examples that we have seen of how this can be done: Batch ETL with Azure Data Factory and Azure Databricks: In this pattern, Azure Data Factory is used to orchestrate and schedule batch ETL processes. Azure Blob Storage serves as the data lake to store raw data. Azure Machine Learning).

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

OCTOBER 23, 2024

response = client.create( key="test", value="Test value", description="Test description" ) print(response) print("nListing all variables.") variables = client.list() print(variables) print("nGetting the test variable.") Creating a test variable. Creating a test variable. Creating a test variable.

Interactive 94

Interactive Testing Data-driven Data Lake 94

O'Reilly on Data

OCTOBER 19, 2021

We need robust versioning for data, models, code, and preferably even the internal state of applications—think Git on steroids to answer inevitable questions: What changed? The applications must be integrated to the surrounding business systems so ideas can be tested and validated in the real world in a controlled manner.

IT 350

IT Testing Experimentation Software 350

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

Data Warehouse 79

Data Warehouse Data Transformation Testing Data Lake 79

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. Additionally, data is extracted from vendor APIs that includes data related to product, marketing, and customer experience.

Data Warehouse 97

Data Warehouse Analytics Data Lake Data Science 97

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. This will enable right-sizing the Redshift data warehouse to meet workload demands cost-effectively. Additional considerations – Factor in additional tasks beyond schema conversion.

Data Warehouse 92

Data Warehouse KPI Optimization Cost-Benefit 92

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 firm also worked on creating a solid pipeline from the data warehouse to the data lake.

Data Lake 75

Data Lake Data Warehouse Data Architecture Reporting 75

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 Warehouse Data Architecture Metadata 86

AWS Big Data

NOVEMBER 9, 2023

A modern data platform entails maintaining data across multiple layers, targeting diverse platform capabilities like high performance, ease of development, cost-effectiveness, and DataOps features such as CI/CD, lineage, and unit testing. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 111

Data Warehouse Testing Data Quality Reporting 111

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Speed changes everything, and continuous testing across the entire CI/CD lifecycle is the key. Tricentis instills that confidence by providing software tools that enable Agile Continuous Testing (ACT) at scale.

Software 52

Software Data Lake Testing Cost-Benefit 52

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

AWS Big Data

NOVEMBER 6, 2024

Second, because traditional data warehousing approaches are unable to keep up with the volume, velocity, and variety of data, engineering teams are building data lakes and adopting open data formats such as Parquet and Apache Iceberg to store their data. Choose Send data. For Version select $LATEST.

Metadata 102

Metadata Data Lake Management Internet of Things 102

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 90

Enterprise Data Warehouse Data Lake Optimization 90

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. A question arises on what level of details we need to include in the table metadata.

Metadata 82

Metadata Data Lake Modeling Data Warehouse 82

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. . Predict – Data Engineering (Apache Spark). 3) Data Visualization is in Tech Preview on AWS and Azure. This is Now.

Data Warehouse 95

Data Warehouse Machine Learning Visualization Data Lake 95

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 72

Optimization Data Lake Cost-Benefit Reporting 72

AWS Big Data

FEBRUARY 6, 2023

Clean up After you complete all the steps and finish testing, complete the following steps to delete resources to avoid incurring costs: On the AWS CloudFormation console, choose the stack you created. He has a specialty in big data services and technologies and an interest in building customer business outcomes together.

Dashboards 76

Dashboards Optimization Data Lake Cost-Benefit 76

AWS Big Data

FEBRUARY 8, 2023

This approach doesn’t solve for data quality issues in source systems, and doesn’t remove the need to have a wholistic data quality strategy. For addressing data quality challenges in Amazon Simple Storage Service (Amazon S3) data lakes and data pipelines, AWS has announced AWS Glue Data Quality (preview).

Data Quality 77

Data Quality Testing Data Warehouse Unstructured Data 77

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. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 70

Reporting Metrics Optimization Data Lake 70

AWS Big Data

JUNE 29, 2023

In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities. View the stream data. Transform and enrich the data. Manipulate the data with Python.

Data Analytics 78

Data Analytics Analytics IoT Data Lake 78

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. How you can get started today Test out watsonx.ai and watsonx.data for yourself with our watsonx trial experience. Within the watsonx.ai

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Alation

MARCH 22, 2022

This produces end-to-end lineage so business and technology users alike can understand the state of a data lake and/or lake house. They can better understand data transformations, checks, and normalization. They can better grasp the purpose and use for specific data (and improve the pipeline!).

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

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. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

OCTOBER 30, 2024

Amazon DataZone now launched authentication supports through the Amazon Athena JDBC driver, allowing data users to seamlessly query their subscribed data lake assets via popular business intelligence (BI) and analytics tools like Tableau, Power BI, Excel, SQL Workbench, DBeaver, and more. Choose Test connection.

Visualization 110

Visualization Data Lake Testing Data Governance 110

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 110

Data Lake Management Metrics Data Warehouse 110

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 96

Data Lake Data Warehouse B2B Data-driven 96

CIO Business Intelligence

AUGUST 7, 2024

The Project Kernel framework utilizes templates and AI augmentation to streamline coding processes, with the AI augmentation generating test cases using training models built on the organization’s data, use cases, and past test cases. This enabled the team to expose the technology to a small group of senior leaders to test.

IT 119

IT Insurance Cost-Benefit Testing 119

AWS Big Data

OCTOBER 30, 2024

Amazon DataZone recently announced the expansion of data analysis and visualization options for your project-subscribed data within Amazon DataZone using the Amazon Athena JDBC driver. Joel has led data transformation projects on fraud analytics, claims automation, and Master Data Management.

Analytics 96

Analytics Visualization Data Governance Data-driven 96

CIO Business Intelligence

OCTOBER 11, 2022

The goal, she explained, is to knock down data silos between those groups, using multiple data lakes supported by strong security and governance, to drive positive impact across the supply chain, manufacturing, and the clinical trials of new drugs. . Accelerating drug discovery and clinical trials.

Machine Learning 145

Machine Learning Data-driven Data Science Testing 145

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. Start your journey with a test drive and sign-up for a 60-day trial to see how CDP can help.

Data Lake 93

Data Lake Cost-Benefit Data-driven Dashboards 93

AWS Big Data

APRIL 5, 2023

Showpad also struggled with data quality issues in terms of consistency, ownership, and insufficient data access across its targeted user base due to a complex BI access process, licensing challenges, and insufficient education. The company also used the opportunity to reimagine its data pipeline and architecture.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

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