AWS Big Data

DECEMBER 16, 2024

For each service, you need to learn the supported authorization and authentication methods, data access APIs, and framework to onboard and test data sources. This approach simplifies your data journey and helps you meet your security requirements. Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

Visualization 71

Visualization Data Processing Testing Publishing 71

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. This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g.,

Data Quality 241

Data Quality Metrics Data-driven Management 241

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

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 103

Analytics Visualization Data Governance Data-driven 103

CIO Business Intelligence

JANUARY 19, 2024

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Check out our list of top big data and data analytics certifications.)

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics and data science are closely related.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

AWS Big Data

APRIL 12, 2023

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows organizations to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). The solution uses the TPC-DS dataset and unmodified data schema and table relationships, but derives queries from TPC-DS to support the SparkSQL test cases.

Testing 85

Testing Big Data Metadata Optimization 85

AWS Big Data

OCTOBER 14, 2024

Amazon Athena provides interactive analytics service for analyzing the data in Amazon Simple Storage Service (Amazon S3). Amazon Redshift is used to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes.

Metadata 88

Metadata Data Lake Modeling Data Warehouse 88

AWS Big Data

JUNE 19, 2024

SELECT * FROM svv_attached_masking_policy; Now you can test that different users can see the same data masked differently based on their roles. The OBJECT_TRANSFORM function in Amazon Redshift is designed to facilitate data transformations by allowing you to manipulate JSON data directly within the database.

Data Warehouse 102

Data Warehouse Testing Sales Structured Data 102

AWS Big Data

AUGUST 9, 2023

The advent of rapid adoption of serverless data lake architectures—with ever-growing datasets that need to be ingested from a variety of sources, followed by complex data transformation and machine learning (ML) pipelines—can present a challenge. Disable the rules after testing to avoid repeated messages.

Data Lake 93

Data Lake Metrics Cost-Benefit Testing 93

AWS Big Data

OCTOBER 18, 2023

To run HiveQL-based data workloads with Spark on Kubernetes mode, engineers must embed their SQL queries into programmatic code such as PySpark, which requires additional effort to manually change code. Navigate to the side menu Virtual clusters , then select the HiveDemo cluster , You can see an entry for the SparkSQL test job.

Big Data 91

Big Data Data Processing Interactive Testing 91

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 118

Data Warehouse Testing Data Quality Reporting 118

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 99

Data Warehouse KPI Optimization Cost-Benefit 99

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 116

Data Lake Management Metrics Data Warehouse 116

AWS Big Data

JULY 18, 2024

For example, the following creates a collection called test with one shard and no replicas. For the updateRequestProcessorChain , OpenSearch provides the ingest pipeline , allowing the enrichment or transformation of data before indexing. Multiple processor stages can be chained to form a pipeline for data transformation.

Dashboards 98

Dashboards Testing Data-driven Visualization 98

AWS Big Data

NOVEMBER 15, 2023

Each CDH dataset has three processing layers: source (raw data), prepared (transformed data in Parquet), and semantic (combined datasets). It is possible to define stages (DEV, INT, PROD) in each layer to allow structured release and test without affecting PROD.

Analytics 106

Analytics Dashboards Metadata Data Warehouse 106

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 101

Metadata Data Lake Visualization Data Quality 101

AWS Big Data

JULY 26, 2023

To grow the power of data at scale for the long term, it’s highly recommended to design an end-to-end development lifecycle for your data integration pipelines. The following are common asks from our customers: Is it possible to develop and test AWS Glue data integration jobs on my local laptop?

Data Integration 79

Data Integration Snapshot Testing Visualization 79

Smart Data Collective

APRIL 29, 2020

The techniques for managing organisational data in a standardised approach that minimises inefficiency. Extraction, Transform, Load (ETL). The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. Microsoft Azure.

Management 97

Management Data Warehouse Digital Transformation Dashboards 97

Cloudera

OCTOBER 14, 2020

Natively support Big Data workloads. YuniKorn is designed for Big Data app workloads, and it natively supports to run Spark/Flink/Tensorflow, etc efficiently in K8s. The Test and Development queue have fixed resource limits. Resource fairness. Default scheduler focuses for long-running services. Acknowledgments.

Machine Learning 118

Machine Learning Management Big Data Optimization 118

AWS Big Data

JANUARY 30, 2025

Our approach The migration initiative consisted of two main parts: building the new architecture and migrating data pipelines from the existing tool to the new architecture. Often, we would work on both in parallel, testing one component of the architecture while developing another at the same time.

Data Warehouse 52

Data Warehouse Data Architecture Machine Learning Data Transformation 52

AWS Big Data

AUGUST 9, 2024

AWS offers Redshift Test Drive to validate whether the configuration chosen for Amazon Redshift is ideal for your workload before migrating the production environment. At this point, only one-time queries and those made by Amazon QuickSight reached the new cluster. We removed the DC2 cluster and completed the migration.

Data Lake 107

Data Lake Analytics Data Warehouse Data-driven 107

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. .

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

AWS Big Data

JULY 6, 2023

It has not been specifically designed for heavy data transformation tasks. To load the time series for a specific point into a pandas data frame, you can use the awswrangler library from your Python code: import awswrangler as wr import pandas as pd # Retrieving the data directly from Amazon S3 df = wr.s3.read_parquet("s3://

Machine Learning 136

Machine Learning Visualization IoT Digital Transformation 136

AWS Big Data

DECEMBER 21, 2023

The data products from the Business Vault and Data Mart stages are now available for consumers. smava decided to use Tableau for business intelligence, data visualization, and further analytics. The data transformations are managed with dbt to simplify the workflow governance and team collaboration.

Data Lake 103

Data Lake Data Warehouse Data-driven B2B 103

AWS Big Data

AUGUST 26, 2024

Duplicating data from a production database to a lower or lateral environment and masking personally identifiable information (PII) to comply with regulations enables development, testing, and reporting without impacting critical systems or exposing sensitive customer data. PII detection and scrubbing.

Visualization 107

Visualization Metadata Data Transformation Testing 107

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 83

Dashboards Optimization Data Lake Cost-Benefit 83

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

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering. Validate and test through the entire migration. Sirius can help.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

AWS Big Data

JULY 27, 2023

DataBrew is a visual data preparation tool that enables you to clean and normalize data without writing any code. The over 200 transformations it provides are now available to be used in an AWS Glue Studio visual job. Big Data Architect on the AWS Glue team. Gonzalo Herreros is a Sr.

Visualization 89

Visualization Cost-Benefit Data Quality Publishing 89

AWS Big Data

JUNE 20, 2023

Kinesis Data Firehose is a fully managed service for delivering near-real-time streaming data to various destinations for storage and performing near-real-time analytics. You can perform analytics on VPC flow logs delivered from your VPC using the Kinesis Data Firehose integration with Datadog as a destination.

Dashboards 92

Dashboards Visualization Metrics Data Transformation 92

AWS Big Data

NOVEMBER 13, 2023

Creating an external schema from the data share database on the consumer, mirroring that of the producer cluster with identical names. Testing: Conducting an internal week-long regression testing and auditing process to meticulously validate all data points by running the same workload and twice the workload.

Data Warehouse 104

Data Warehouse Analytics Data Lake Data Science 104

AWS Big Data

FEBRUARY 8, 2023

Jessicamouth 2964 Queensland Load the dataset First, create a new table in your Redshift Serverless endpoint and copy the test data into it by doing the following: Open the Query Editor V2 and log in using the admin user name and details defined when the endpoint was created.

Data Quality 84

Data Quality Testing Data Warehouse Unstructured Data 84

Alation

FEBRUARY 20, 2020

In perhaps a preview of things to come next year, we decided to test how a Data Catalog might work with Tableau on the same data. You can check out a self service data prep flow from catalog to viz in this recorded version here. Rita Sallam Introduces the Data Prep Rodeo. To Coming Home, Home on the Range.

Scorecard 52

Scorecard ROI Data-driven Visualization 52

AWS Big Data

MAY 9, 2023

AWS Glue Studio is a graphical interface that makes it easy to create, run, and monitor extract, transform, and load (ETL) jobs in AWS Glue. It allows you to visually compose data transformation workflows using nodes that represent different data handling steps, which later are converted automatically into code to run.

Visualization 86

Visualization Marketing Big Data IT 86

Alation

JANUARY 17, 2023

Extract, load, Transform (ELT) tools. Data ingestion/integration services. Data orchestration tools. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? Reverse ETL tools.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

AWS Big Data

APRIL 25, 2024

Alternatively, you can use AWS Glue for Apache Spark, which provides built-in support for bucketing configurations during the data transformation process. AWS Glue allows you to define bucketing parameters, such as the number of buckets and the columns to bucket on, providing an optimized data layout for efficient querying with Athena.

Optimization 72

Optimization Data Lake Cost-Benefit Reporting 72