Cloudera

DECEMBER 9, 2022

Developers need to onboard new data sources, chain multiple data transformation steps together, and explore data as it travels through the flow. This allows developers to make changes to their processing logic on the fly while running some test data through their flow and validating that their changes work as intended.

Testing 100

Testing Cost-Benefit Interactive Visualization 100

CIO Business Intelligence

APRIL 8, 2025

Build data validation rules directly into ingestion layers so that insufficient data is stopped at the gate and not detected after damage is done. Use lineage tooling to trace data from source to report. Understanding how data transforms and where it breaks is crucial for audibility and root-cause resolution.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

datapine

SEPTEMBER 29, 2022

Also known as data validation, integrity refers to the structural testing of data to ensure that the data complies with procedures. This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g., Here, it all comes down to the data transformation error rate.

Data Quality 241

Data Quality Metrics Data-driven Management 241

CIO Business Intelligence

JULY 5, 2022

What is the difference between business analytics and data analytics? Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

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. These event changes are also routed to the same SNS topic.

Data Lake 93

Data Lake Metrics Cost-Benefit Testing 93

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

Sisense

AUGUST 28, 2020

All this contributes to your overall data integrity profile. Logical data integrity is designed to guard against human error. We’ll explore this concept in detail in the testing section below. Data integrity: A process and a state. There are two means for ensuring data integrity: process and testing.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

Cloudera

MARCH 14, 2023

Allows them to iteratively develop processing logic and test with as little overhead as possible. Plays nice with existing CI/CD processes to promote a data pipeline to production. Provides monitoring, alerting, and troubleshooting for production data pipelines.

Testing 84

Testing Publishing Metadata Interactive 84

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

MARCH 13, 2024

Using EventBridge integration, filtered positional updates are published to an EventBridge event bus. Amazon Location device position events arrive on the EventBridge default bus with source: ["aws.geo"] and detail-type: ["Location Device Position Event"]. In this model, the Lambda function is invoked for each incoming event.

Analytics 109

Analytics IoT Metadata Internet of Things 109

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

AWS Big Data

OCTOBER 11, 2023

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.

Management 117

Management Metadata Analytics Dashboards 117

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

APRIL 25, 2023

On many occasions, they need to apply business logic to the data received from the source SaaS platform before pushing it to the target SaaS platform. AnyCompany’s marketing team hosted an event at the Anaheim Convention Center, CA. The marketing team created leads based on the event in Adobe Marketo. Let’s take an example.

Sales 79

Sales Visualization Software Metadata 79

Cloudera

JULY 21, 2022

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Cloudera Data Warehouse). Apache Hive.

Metrics 87

Metrics Slice and Dice Data Warehouse Dashboards 87

Sisense

AUGUST 6, 2020

Be sure test cases represent the diversity of app users. As an AI product manager, here are some important data-related questions you should ask yourself: What is the problem you’re trying to solve? What data transformations are needed from your data scientists to prepare the data? The perfect fit.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

AWS Big Data

NOVEMBER 13, 2023

The upstream data pipeline is a robust system that integrates various data sources, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK) for handling clickstream events, Amazon Relational Database Service (Amazon RDS) for delta transactions, and Amazon DynamoDB for delta game-related information.

Data Warehouse 104

Data Warehouse Analytics Data Lake Data Science 104

CIO Business Intelligence

JUNE 13, 2022

Angel-Johnson says she, too, has a heightened level of concern around security issues and more specifically data protection. I thought I was hired for digital transformation but what is really needed is a data transformation,” she says. To get there, Angel-Johnson has embarked on a master data management initiative.

IT 144

IT Digital Transformation Internet of Things Strategy 144

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

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

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

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

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 76

Reporting Metrics Optimization Data Lake 76

Cloudera

OCTOBER 14, 2020

The Test and Development queue have fixed resource limits. YuniKorn is also compatible with the management commands and utilities, such as cordon nodes, retrieving events via kubectl, etc. Cloudera’s CDP platform offers Cloudera Data Engineering experience which is powered by Apache YuniKorn (Incubating). Acknowledgments.

Machine Learning 118

Machine Learning Management Big Data Optimization 118

Cloudera

OCTOBER 8, 2024

Detailed Data and Model Lineage Tracking*: Ensures comprehensive tracking and documentation of data transformations and model lifecycle events, enhancing reproducibility and auditability.

Optimization 75

Optimization Experimentation Metrics Enterprise 75

AWS Big Data

APRIL 27, 2023

With these features, you can now build data pipelines completely in standard SQL that are serverless, more simple to build, and able to operate at scale. Typically, data transformation processes are used to perform this operation, and a final consistent view is stored in an S3 bucket or folder.

Data Lake 81

Data Lake Snapshot Optimization Data Transformation 81

Domino Data Lab

AUGUST 20, 2019

The problem is that a new unique identifier of a test example won’t be anywhere in the tree. Feature extraction means moving from low-level features that are unsuitable for learning—practically speaking, we get poor testing results—to higher-level features which are useful for learning. Separate out a hold-out test set.

Testing 68

Testing Modeling Interactive Measurement 68

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. Apache Spark is the engine that runs the jobs created on AWS Glue Studio.

Visualization 89

Visualization Cost-Benefit Data Quality Publishing 89

Ontotext

APRIL 4, 2019

Within a large enterprise, there is a huge amount of data accumulated over the years – many decisions have been made and different methods have been tested. We minimized the time between the event (and what the journalist wanted to say about it) and the moment the reader or viewer could consume it.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

AWS Big Data

OCTOBER 31, 2023

Customers rely on data from different sources such as mobile applications, clickstream events from websites, historical data, and more to deduce meaningful patterns to optimize their products, services, and processes. If you’re testing on a different Amazon MWAA version, update the requirements file accordingly.

Data Processing 102

Data Processing Management Publishing Visualization 102

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective?

Metrics 52

Metrics Dashboards Sales Reporting 52

AWS Big Data

FEBRUARY 21, 2023

We use Apache Spark as our main data processing engine and have over 1,000 Spark applications running over massive amounts of data every day. These Spark applications implement our business logic ranging from data transformation, machine learning (ML) model inference, to operational tasks. Their costs were climbing.

Cost-Benefit 59

Cost-Benefit Informatics Optimization Management 59

AWS Big Data

FEBRUARY 6, 2023

Transform the YARN job history logs from JSON to CSV After obtaining YARN logs, you run a YARN log organizer, yarn-log-organizer.py, which is a parser to transform JSON-based logs to CSV files. The parser also has other capabilities, including sorting events by time, removing dedicates, and merging multiple logs. Choose Delete.

Dashboards 83

Dashboards Optimization Data Lake Cost-Benefit 83

AWS Big Data

JULY 31, 2023

You can examine various events from the stack creation process on the Events tab. Select the connection again and on the Actions menu, choose Test connection. Testing the connection can take approximately 1 minute. You will see the message “Successfully connected to the data store with connection blog-redshift-connection.”

Sales 52

Sales Data Warehouse Visualization Testing 52

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 84

Data Analytics Analytics IoT Data Lake 84

Peter James Thomas

OCTOBER 30, 2018

It may well be that one thing that a CDO needs to get going is a data transformation programme. This may purely be focused on cultural aspects of how an organisation records, shares and otherwise uses data. It may be to build a new (or a first) Data Architecture. Establishing a regular Data Audit.

Marketing 51

Marketing Strategy Data Architecture Data Strategy 51

DataRobot Blog

APRIL 4, 2022

More often than I would like to admit, I have heard the following phrase from a client: “We do not have the data for the five media campaigns we ran last year, but we have data for the other four. The classical approach is to assume the adstock function (typically linear ) and test out various values of ?

Machine Learning 52

Machine Learning Sales Measurement ROI 52