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

O'Reilly on Data

OCTOBER 19, 2021

With these five layers, we can present a highly productive, data-centric software interface that enables iterative development of large-scale data-intensive applications. However, none of these layers help with modeling and optimization. Model Operations. Model Development.

IT 364

IT Testing Experimentation Software 364

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

AWS Big Data

NOVEMBER 22, 2024

Maintaining reusable database sessions to help optimize the use of database connections, preventing the API server from exhausting the available connections and improving overall system scalability.

Data Warehouse 104

Data Warehouse Recreation/Entertainment Cost-Benefit Data-driven 104

AWS Big Data

APRIL 25, 2024

Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making. However, as data volumes continue to grow, optimizing data layout and organization becomes crucial for efficient querying and analysis.

Optimization 72

Optimization Data Lake Cost-Benefit Reporting 72

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

NOVEMBER 27, 2024

Together with price-performance, Amazon Redshift offers capabilities such as serverless architecture, machine learning integration within your data warehouse and secure data sharing across the organization. dbt Cloud is a hosted service that helps data teams productionize dbt deployments.

Data Warehouse 108

Data Warehouse Analytics Testing Modeling 108

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. How is Data Virtualization performance optimized? In improving operational processes.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

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

NOVEMBER 15, 2023

BMW Group uses 4,500 AWS Cloud accounts across the entire organization but is faced with the challenge of reducing unnecessary costs, optimizing spend, and having a central place to monitor costs. The ultimate goal is to raise awareness of cloud efficiency and optimize cloud utilization in a cost-effective and sustainable manner.

Dashboards 111

Dashboards Analytics Metadata Data Warehouse 111

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. This includes the ETL processes that capture source data, the functional refinement and creation of data products, the aggregation for business metrics, and the consumption from analytics, business intelligence (BI), and ML.

Data Warehouse 113

Data Warehouse KPI Optimization Cost-Benefit 113

AWS Big Data

OCTOBER 14, 2024

Adding data transformation details to metadata can be challenging because of the dispersed nature of this information across data processing pipelines, making it difficult to extract and incorporate into table-level metadata. Enriching the prompt You can enhance the prompts with query optimization rules like partition pruning.

Metadata 103

Metadata Data Lake Modeling Data Warehouse 103

AWS Big Data

APRIL 11, 2023

Accurately predicting demand for products allows businesses to optimize inventory levels, minimize stockouts, and reduce holding costs. Solution overview In today’s highly competitive business landscape, it’s essential for retailers to optimize their inventory management processes to maximize profitability and improve customer satisfaction.

Forecasting 96

Forecasting Management IoT Data-driven 96

AWS Big Data

SEPTEMBER 5, 2024

With auto-copy, automation enhances the COPY command by adding jobs for automatic ingestion of data. If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

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 112

Dashboards Testing Data-driven Visualization 112

datapine

SEPTEMBER 29, 2022

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. In other words, it measures the time between when data is expected and the moment when it is readily available for use. date, month, and year).

Data Quality 241

Data Quality Metrics Data-driven Management 241

DataKitchen

DECEMBER 9, 2022

By providing real-time visibility into the performance and behavior of data-related systems, DataOps observability enables organizations to identify and address issues before they become critical, and to optimize their data-related workflows for maximum efficiency and effectiveness.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

AWS Big Data

JULY 25, 2024

If you want deeper control over your infrastructure for cost and latency optimization, you can choose OpenSearch Service’s managed clusters deployment option. With managed clusters, you get granular control over the instances you would like to use, indexing and data-sharding strategy, and more.

Cost-Benefit 126

Cost-Benefit Machine Learning Dashboards Management 126

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

CIO Business Intelligence

JANUARY 19, 2024

The certification consists of several exams that cover topics such as machine learning, natural language processing, computer vision, and model forecasting and optimization. You should also have experience with pattern detection, experimentation in business optimization techniques, and time-series forecasting.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

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). This performance-optimized runtime offered by Amazon EMR makes your Spark jobs run fast and cost-effectively. As of the Amazon EMR 6.5 Amazon EMR 6.10

Testing 101

Testing Big Data Metadata Optimization 101

AWS Big Data

AUGUST 9, 2024

After the read query validation stage was complete and we were satisfied with the performance, we reconnected our orchestrator so that the data transformation queries could be run in the new cluster. At this point, only one-time queries and those made by Amazon QuickSight reached the new cluster.

Data Lake 111

Data Lake Analytics Data Warehouse Data-driven 111

Cloudera

OCTOBER 13, 2020

Data Warehouse – in addition to a number of performance optimizations, DW has added a number of new features for better scalability, monitoring and reliability to enable self-service access with security and performance . Predict – Data Engineering (Apache Spark). New Services. Learn More, Keep in Touch.

Data Warehouse 97

Data Warehouse Machine Learning Visualization Data Lake 97

Occam's Razor

OCTOBER 19, 2010

A huge vast majority of clicks coming from search engines continue to be organic clicks (which is why I love and adore search engine optimization). Google Website Optimizer. Here's a free guide – 26 pages – to use the website optimizer optimally: PDF Download: The Techie Guide to Google Website Optimizer.

Analytics 136

Analytics Testing Measurement Optimization 136

AWS Big Data

MAY 3, 2023

In this post, we provide a detailed overview of streaming messages with Amazon Managed Streaming for Apache Kafka (Amazon MSK) and Amazon ElastiCache for Redis , covering technical aspects and design considerations that are essential for achieving optimal results. We also discuss the key features, considerations, and design of the solution.

IoT 111

IoT Internet of Things Data Transformation Management 111

CIO Business Intelligence

FEBRUARY 16, 2023

But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. Digitizing was our first stake at the table in our data journey,” he says. The offensive side?

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

AWS Big Data

MAY 9, 2023

For workloads such as data transforms, joins, and queries, you can use G.1X With exponentially growing data sources and data lakes, customers want to run more data integration workloads, including their most demanding transforms, aggregations, joins, and queries. 1X (1 DPU) and G.2X DPU-hour ($) G.2X

Data Lake 110

Data Lake Cost-Benefit Data Integration Data Transformation 110

AWS Big Data

APRIL 27, 2023

It supports modern analytical data lake operations such as create table as select (CTAS), upsert and merge, and time travel queries. Athena also supports the ability to create views and perform VACUUM (snapshot expiration) on Apache Iceberg tables to optimize storage and performance. You can perform bulk load using a CTAS statement.

Data Lake 95

Data Lake Snapshot Optimization Data Transformation 95

AWS Big Data

JANUARY 30, 2025

Pattern 1: Data transformation, load, and unload Several of our data pipelines included significant data transformation steps, which were primarily performed through SQL statements executed by Amazon Redshift. The following Diagram 2 shows this workflow.

Data Warehouse 53

Data Warehouse Data Architecture Machine Learning Data Transformation 53

Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. This enabled new use-cases with customers that were using a mix of Spark and Hive to perform data transformations. .

Snapshot 118

Snapshot Data-driven Optimization Data Architecture 118

AWS Big Data

JANUARY 6, 2025

With Amazon AppFlow, you can run data flows at nearly any scale and at the frequency you chooseon a schedule, in response to a business event, or on demand. You can configure data transformation capabilities such as filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps.

Analytics 98

Analytics Data Warehouse Big Data Metrics 98

AWS Big Data

FEBRUARY 6, 2023

Additionally, a TCO calculator generates the TCO estimation of an optimized EMR cluster for facilitating the migration. For optimizing EMR cluster cost effectiveness, the following table provides general guidelines of choosing the proper type of EMR cluster and Amazon Elastic Compute Cloud (Amazon EC2) family.

Dashboards 96

Dashboards Optimization Data Lake Cost-Benefit 96

Cloudera

OCTOBER 8, 2024

This service supports a range of optimized AI models, enabling seamless and scalable AI inference. By leveraging the NVIDIA NeMo platform and optimized versions of open-source models like Llama 3 and Mistral, businesses can harness the latest advancements in natural language processing, computer vision, and other AI domains.

Optimization 75

Optimization Experimentation Metrics Enterprise 75

CIO Business Intelligence

DECEMBER 6, 2023

Notably, a partner with global reach can be particularly valuable to an organisation with operations with a global presence; since the structure of most multinational organisations is optimised to support their core business rather than initiatives like digital transformation.

Digital Transformation 116

Digital Transformation Software Cost-Benefit Manufacturing 116

Sisense

OCTOBER 15, 2020

Let’s look at a few ways that different industries take advantage of streaming data. How industries can benefit from streaming data. Automotive: Monitoring connected, autonomous cars in real time to optimize routes to avoid traffic and for diagnosis of mechanical issues. Optimizing object storage.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

JULY 20, 2023

Specifically, the system uses Amazon SageMaker Processing jobs to process the data stored in the data lake, employing the AWS SDK for Pandas (previously known as AWS Wrangler) for various data transformation operations, including cleaning, normalization, and feature engineering. Orca addressed this in several ways.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

NOVEMBER 16, 2023

Data Vault 2.0 allows for the following: Agile data warehouse development Parallel data ingestion A scalable approach to handle multiple data sources even on the same entity A high level of automation Historization Full lineage support However, Data Vault 2.0

Enterprise 110

Enterprise Data Warehouse Data Lake Optimization 110