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

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

DataKitchen

DECEMBER 9, 2022

The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes. ChatGPT> DataOps is a term that refers to the set of practices and tools that organizations use to improve the quality and speed of data analytics and machine learning.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

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

CIO Business Intelligence

APRIL 30, 2024

Einstein Copilot for Tableau remains in beta, but Tableau announced two new features for the AI assistant as well: AI-assisted data transformation. This feature can automate a data transformation pipeline with step-by-step suggestions for preparing data for analysis.

Analytics 96

Analytics Metrics Visualization Dashboards 96

CIO Business Intelligence

DECEMBER 6, 2023

However, this partnership model cannot keep pace with an always-changing technology landscape in which the skill gaps and lack of resources are increasing. The new models recognise this, drawing tech vendors to shift toward innovation-focused roles and become partners in the client’s success.

Digital Transformation 116

Digital Transformation Software Cost-Benefit Manufacturing 116

AWS Big Data

NOVEMBER 15, 2023

For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. Additionally, it manages table definitions in the AWS Glue Data Catalog , containing references to data sources and targets of extract, transform, and load (ETL) jobs in AWS Glue.

Dashboards 106

Dashboards Analytics Metadata Data Warehouse 106

AWS Big Data

APRIL 26, 2023

The Cloud Data Hub processes and combines anonymized data from vehicle sensors and other sources across the enterprise to make it easily accessible for internal teams creating customer-facing and internal applications. To learn more about the Cloud Data Hub, refer to BMW Group Uses AWS-Based Data Lake to Unlock the Power of Data.

Forecasting 129

Forecasting Manufacturing Data Lake Big Data 129

IBM Big Data Hub

OCTOBER 16, 2023

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models can use language, vision and more to affect the real world.

Risk 70

Risk Modeling Management Metadata 70

CIO Business Intelligence

JUNE 29, 2022

Taking the broadest possible interpretation of data analytics , Azure offers more than a dozen services — and that’s before you include Power BI, with its AI-powered analysis and new datamart option , or governance-oriented approaches such as Microsoft Purview. Azure Data Factory. Azure Synapse Analytics. Analytics, Microsoft Azure

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

AWS Big Data

AUGUST 6, 2024

Amazon Redshift ML is a feature of Amazon Redshift that enables you to build, train, and deploy machine learning (ML) models directly within the Redshift environment. Generative AI models can derive new features from your data and enhance decision-making. Create a materialized view to load the raw streaming data.

Data Warehouse 84

Data Warehouse Data-driven Modeling Internet of Things 84

AWS Big Data

NOVEMBER 16, 2023

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault. Data Vault 2.0

Enterprise 97

Enterprise Data Warehouse Data Lake Optimization 97

AWS Big Data

AUGUST 19, 2024

Efficient data integration – AWS Glue simplifies the ETL process, providing a scalable and flexible solution for data integration between Snowflake and Amazon S3. Scalability and flexibility – The architecture supports scalable data transfers and can be extended to integrate additional data sources and destinations as needed.

Analytics 107

Analytics Data-driven Data Integration Data Lake 107

AWS Big Data

JANUARY 30, 2025

We set up our AWS CDK to refer to the contents of a specific directory and define a resource (for example, an AWS Step Functions state machine or an AWS Glue job) for each file it found in that directory. We also used it as a repository for storing code that could be retrieved and used by other services.

Data Warehouse 52

Data Warehouse Data Architecture Machine Learning Data Transformation 52

AWS Big Data

AUGUST 1, 2023

For full instructions, refer to Jira Cloud connector for Amazon AppFlow. You can do this by updating the CloudFormation stack with a flag that includes the CDC and data transformation steps. This will enable both the CDC steps and the data transformation steps for the Jira data. Choose Update.

Data Lake 92

Data Lake Data Transformation Data-driven Cost-Benefit 92

AWS Big Data

FEBRUARY 6, 2023

Operationalizing machine learning (ML) is another growing use case, where data has to be transformed and normalized before it can be loaded into an ML model. In both use cases, the data pipeline is preparing the data for consumption by ingesting data from different sources and transforming it through a series of steps.

Management 91

Management Interactive Publishing Metadata 91

AWS Big Data

SEPTEMBER 5, 2024

If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported. In scenarios where data transformation is required, you can use Redshift stored procedures to modify data in Redshift tables.

IoT 106

IoT Data Warehouse Cost-Benefit Reporting 106

AWS Big Data

OCTOBER 11, 2023

Under the Transparency in Coverage (TCR) rule , hospitals and payors to publish their pricing data in a machine-readable format. For more information, refer to Delivering Consumer-friendly Healthcare Transparency in Coverage On AWS. The Data Catalog now contains references to the machine-readable data.

Visualization 110

Visualization Dashboards Data-driven Gap analysis 110

AWS Big Data

APRIL 19, 2023

Encounter 4 appears to refer to the customer with ID 8, but the email doesn’t match, and no Customer_ID is given. A knowledge graph allows us to combine data from different sources to gain a better understanding of a specific problem domain. With the AWS SDK for Pandas, we combine this data by running a query against the Neptune graph.

Technology 92

Technology Data-driven Machine Learning Sales 92

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. As a result, alternative data integration technologies (e.g.,

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94

AWS Big Data

MARCH 13, 2024

You can modify the Lambda function to fetch additional vehicle information from a separate data store (for example, a DynamoDB table or a Customer Relationship Management system) to enrich the data, before storing the results in an S3 bucket. In this model, the Lambda function is invoked for each incoming event.

Analytics 109

Analytics IoT Metadata Internet of Things 109

AWS Big Data

DECEMBER 21, 2023

OpenSearch Service also has vector database capabilities that let you implement semantic search and Retrieval Augmented Generation (RAG) with large language models (LLMs) to build recommendation and media search engines. For setup instructions, refer to Getting started with Amazon OpenSearch Service.

Analytics 107

Analytics IT Data Lake Visualization 107

Peter James Thomas

MARCH 9, 2020

However, in this initial article, I wanted to to focus on one tool that I have used as part of my Data Strategy engagements; a Data Maturity Model. I used to talk about carrying out a Situational Analysis of Data Capabilities, nowadays I am more likely to refer to a Data Capability Review.

Measurement 67

Measurement Data Strategy Strategy Modeling 67

AWS Big Data

MARCH 15, 2023

To populate the database, the Infomedia team developed a data pipeline using Amazon Simple Storage Service (Amazon S3) for data storage, AWS Glue for data transformations, and Apache Hudi for CDC and record-level updates.

Cost-Benefit 72

Cost-Benefit Data Processing Optimization Data-driven 72

AWS Big Data

MARCH 16, 2023

A source of unpredictable workloads is dbt Cloud , which SafetyCulture uses to manage data transformations in the form of models. Whenever models are created or modified, a dbt Cloud CI job is triggered to test the models by materializing the models in Amazon Redshift.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 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 85

Visualization Marketing Big Data IT 85

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture.

Data Governance 76

Data Governance Business Objectives Data Quality Measurement 76

AWS Big Data

AUGUST 26, 2024

In this post, I’ll walk you through how to copy data from one Amazon Relational Database Service (Amazon RDS) for PostgreSQL database to another, while scrubbing PII along the way using AWS Glue. Built-in data transformations then scrub columns containing PII using pre-defined masking functions. PII detection and scrubbing.

Visualization 107

Visualization Metadata Data Transformation Testing 107

Domino Data Lab

AUGUST 20, 2019

Feature engineering is useful for data scientists when assessing tradeoff decisions regarding the impact of their ML models. It is a framework for approaching ML as well as providing techniques for extracting features from raw data that can be used within the models. Feature Engineering Terminology and Motivation.

Testing 68

Testing Modeling Interactive Measurement 68

Jet Global

MAY 28, 2019

A data warehouse stores transactional level details and serves the broader reporting and analytical needs of an organization – creating one source of truth for building semantic models or serving structured, simplified and harmonized data to tools like Power BI, Excel or even SSRS.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

AWS Big Data

JANUARY 17, 2024

By preserving historical versions, data lake time travel provides benefits such as auditing and compliance, data recovery and rollback, reproducible analysis, and data exploration at different points in time. Another popular transaction data lake use case is incremental query. Make sure you are in the us-east-1 Region.

Data Lake 107

Data Lake Snapshot Big Data Data-driven 107

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. For an example, refer to How JPMorgan Chase built a data mesh architecture to drive significant value to enhance their enterprise data platform. Platform architects define a well-architected platform.

Data Warehouse 99

Data Warehouse KPI Optimization Cost-Benefit 99

DataRobot Blog

APRIL 4, 2022

MMM stands for Marketing Mix Model and it is one of the oldest and most well-established techniques to measure the sales impact of marketing activity statistically. Data Requirements. As with any type of statistical model, data is key and GIGO (“Garbage In, Garbage Out”) principle definitely applies. What is MMM?

Machine Learning 52

Machine Learning Sales Measurement ROI 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

Ontotext

AUGUST 24, 2023

The solution is choosing one of the standard provenance models. Standard provenance models Graph Replace is probably the most straightforward model. Trade-offs of the standard provenance models Graph Replace is fast and simple to implement and we recommend it to people with batch updates. Persistent or non-persistent IDs?

Data Integration 52

Data Integration Modeling Business Objectives Optimization 52

AWS Big Data

APRIL 25, 2023

The following AWS services are used for data ingestion, processing, and load: Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between SaaS applications like Salesforce, SAP, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift , in just a few clicks.

Sales 78

Sales Visualization Software Metadata 78