KDnuggets

OCTOBER 3, 2024

Learn the data engineering tools for data orchestration, database management, batch processing, ETL (Extract, Transform, Load), data transformation, data visualization, and data streaming.

Visualization 139

Visualization Data Transformation Management 139

Rocket-Powered Data Science

MARCH 20, 2023

Content includes reports, documents, articles, presentations, visualizations, video, and audio representations of the insights and knowledge that have been extracted from data. We could further refine our opening statement to say that our business users are too often in a state of being data-rich, but insights-poor, and content-hungry.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

AWS Big Data

AUGUST 26, 2024

You can use AWS Glue Studio to set up data replication and mask PII with no coding required. AWS Glue Studio visual editor provides a low-code graphic environment to build, run, and monitor extract, transform, and load (ETL) scripts. Data transformation – Adjusts and removes unnecessary fields.

Visualization 107

Visualization Metadata Data Transformation Testing 107

AWS Big Data

JULY 27, 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. DataBrew is a visual data preparation tool that enables you to clean and normalize data without writing any code. Choose Visual with a blank canvas and create the visual job.

Visualization 89

Visualization Cost-Benefit Data Quality Publishing 89

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

Ontotext

NOVEMBER 18, 2021

And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own. You have to take care of data extraction, transformation and loading, and of visualization.

Visualization 98

Visualization Reporting Metadata Enterprise 98

AWS Big Data

DECEMBER 16, 2024

With the ability to browse metadata, you can understand the structure and schema of the data source, identify relevant tables and fields, and discover useful data assets you may not be aware of. You can navigate to the projects Data page to visually verify the existence of the newly created table. option("url", jdbcurl).option("dbtable",

Visualization 71

Visualization Data Processing Testing Publishing 71

AWS Big Data

JANUARY 15, 2025

In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. This approach supports both the immediate needs of visualization tools such as Tableau and the long-term demands of digital twin and IoT data analytics.

IoT 100

IoT Machine Learning Metadata Data-driven 100

Wayne Yaddow

FEBRUARY 18, 2025

Selecting the strategies and tools for validating data transformations and data conversions in your data pipelines. Introduction Data transformations and data conversions are crucial to ensure that raw data is organized, processed, and ready for useful analysis.

Testing 52

Testing Data Transformation Data-driven Data Quality 52

datapine

MAY 2, 2023

Financial efficiency: One of the key benefits of big data in supply chain and logistics management is the reduction of unnecessary costs. Using the right dashboard and data visualizations, it’s possible to hone in on any trends or patterns that uncover inefficiencies within your processes. Now’s the time to strike.

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

Wayne Yaddow

MARCH 5, 2025

In this post, well see the fundamental procedures, tools, and techniques that data engineers, data scientists, and QA/testing teams use to ensure high-quality data as soon as its deployed. First, we look at how unit and integration tests uncover transformation errors at an early stage. Statistical tests (e.g.,

Testing 52

Testing Data Transformation Statistics Metadata 52

datapine

SEPTEMBER 29, 2022

He/she assists the organization by providing clarity and insight into advanced data technology solutions. As quality issues are often highlighted with the use of dashboard software , the change manager plays an important role in the visualization of data quality. Here, it all comes down to the data transformation error rate.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Wayne Yaddow

FEBRUARY 26, 2025

AI is transforming how senior data engineers and data scientists validate data transformations and conversions. Artificial intelligence-based verification approaches aid in the detection of anomalies, the enforcement of data integrity, and the optimization of pipelines for improved efficiency.

Data Transformation 52

Data Transformation Testing Data-driven Data Quality 52

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

InsightOut

MAY 4, 2021

In this data-driven world, building a team of data analysts can be a challenge. Implementing data visualization and analytics dashboards can be the beginning of the data transformation journey.

Visualization 52

Visualization Dashboards Data-driven Data Transformation 52

FineReport

JUNE 7, 2024

In 2024, data visualization companies play a pivotal role in transforming complex data into captivating narratives. This blog provides an insightful exploration of the leading entities shaping the data visualization landscape.

Visualization 52

Visualization Predictive Analytics Dashboards Predictive Modeling 52

CIO Business Intelligence

APRIL 30, 2024

Together the technologies aim to help business users and “novice” data analysts explore their data and gain insights without having to resort to data experts. This is really empowering everyone to be a data expert,” Maxon said. “It Shared Dimensions and Composable Data Sources.

Analytics 96

Analytics Metrics Visualization Dashboards 96

CIO Business Intelligence

JULY 5, 2022

While quantitative analysis, operational analysis, and data visualizations are key components of business analytics, the goal is to use the insights gained to shape business decisions. What is the difference between business analytics and data analytics? Business analytics is a subset of data analytics.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

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

Cloudera

AUGUST 17, 2021

When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. Typically users need to ingest data, transform it into optimal format with quality checks, and optimize querying of the data by visual analytics tool.

Management 115

Management Cost-Benefit Data Transformation Optimization 115

AWS Big Data

OCTOBER 11, 2023

The availability of machine-readable files opens up new possibilities for data analytics, allowing organizations to analyze large amounts of pricing data. Using machine learning (ML) and data visualization tools, these datasets can be transformed into actionable insights that can inform decision-making.

Visualization 110

Visualization Dashboards Data-driven Gap analysis 110

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

Octopai

MARCH 31, 2021

In other words, kind of like Hansel and Gretel in the forest, your data leaves a trail of breadcrumbs – the metadata – to record where it came from and who it really is. So the first step in any data lineage mapping project is to ensure that all of your data transformation processes do in fact accurately record metadata.

Metadata 133

Metadata Data Transformation Business Intelligence Reporting 133

Jen Stirrup

NOVEMBER 30, 2021

In this session, we will start R right from the beginning, from installing R through to data transformation and integration, through to visualizing data by using R in PowerBI. Then, we will move towards powerful but simple to use datatypes in R such as data frames.

Visualization 92

Visualization Dashboards Data Transformation Publishing 92

Cloudera

OCTOBER 13, 2020

CDP Data Engineering (1) – a service purpose-built for data engineers focused on deploying and orchestrating data transformation using Spark at scale. 3) Data Visualization is in Tech Preview on AWS and Azure. Keep up with what’s new in CDP-PC by following our monthly release summaries. . (1)

Data Warehouse 97

Data Warehouse Machine Learning Visualization Data Lake 97

O'Reilly on Data

JANUARY 17, 2023

That takes us to a conspicuous omission from that list of roles: the data scientists who focused on building basic models. AutoML tools are doing most of that work now, in the same way that the basic dashboards or visualizations are now the domain of self-service tools like AWS QuickSight, Google Data Studio, or Tableau.

Machine Learning 363

Machine Learning Predictive Modeling Software Modeling 363

AWS Big Data

MAY 22, 2024

Amazon OpenSearch Ingestion is a fully managed serverless pipeline that allows you to ingest, filter, transform, enrich, and route data to an Amazon OpenSearch Service domain or Amazon OpenSearch Serverless collection. You can now view the configurations in JSON format in addition to the YAML format and edit them in place.

Data Architecture 112

Data Architecture Visualization Data Transformation Management 112

AWS Big Data

DECEMBER 21, 2023

AWS Glue is a serverless data integration service that makes it straightforward to discover, prepare, and combine data for analytics, machine learning (ML), and application development. AWS Glue provides both visual and code-based interfaces to make data integration effortless. Choose Create job and Visual ETL.

Analytics 107

Analytics IT Data Lake Visualization 107

AWS Big Data

OCTOBER 27, 2023

AWS Glue provides all the capabilities needed for data integration, so you can start analyzing your data and putting it to use in minutes instead of months. AWS Glue provides both visual and code-based interfaces to make data integration easier. Users can more easily find and access data using the AWS Glue Data Catalog.

Analytics 110

Analytics Visualization Data Integration Cost-Benefit 110

AWS Big Data

AUGUST 13, 2024

AWS Glue is a serverless data integration service that helps analytics users to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. For this example, you use AWS Glue Studio to develop a visual ETL pipeline. Select Visual ETL in the central pane.

Data Processing 98

Data Processing Visualization Data Lake Data Processing 98

erwin

APRIL 29, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

AWS Big Data

NOVEMBER 15, 2023

They can use their own toolsets or rely on provided blueprints to ingest the data from source systems. Once released, consumers use datasets from different providers for analysis, machine learning (ML) workloads, and visualization. The difference lies in when and where data transformation takes place.

Dashboards 106

Dashboards Analytics Metadata Data Warehouse 106

DataKitchen

OCTOBER 25, 2022

It’s because it’s a hard thing to accomplish when there are so many teams, locales, data sources, pipelines, dependencies, data transformations, models, visualizations, tests, internal customers, and external customers.

Testing 130

Testing Data-driven Visualization Dashboards 130

AWS Big Data

JULY 18, 2024

The main driving factors include lower total cost of ownership, scalability, stability, improved ingestion connectors (such as Data Prepper , Fluent Bit, and OpenSearch Ingestion), elimination of external cluster managers like Zookeeper, enhanced reporting, and rich visualizations with OpenSearch Dashboards.

Dashboards 98

Dashboards Testing Data-driven Visualization 98

AWS Big Data

DECEMBER 5, 2023

This dynamic tool, powered by AWS and CARTO, provided robust visualizations of which regions and populations were interacting with our survey, enabling us to zoom in quickly and address gaps in coverage. Figure 1: Workflow illustrating data ingesting, transformation, and visualization using Redshift and CARTO.

Measurement 93

Measurement Dashboards Data Warehouse Analytics 93

CIO Business Intelligence

JUNE 29, 2022

But the features in Power BI Premium are now more powerful than the functionality in Azure Analysis Services, so while the service isn’t going away, Microsoft will offer an automated migration tool in the second half of this year for customers who want to move their data models into Power BI instead. Azure Data Factory.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

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