O'Reilly on Data

OCTOBER 19, 2021

If you ask an engineer to show how they operate the application in production, they will likely show containers and operational dashboards—not unlike any other software service. but to reference concrete tooling used today in order to ground what could otherwise be a somewhat abstract exercise. Foundational Infrastructure Layers.

IT 364

IT Testing Experimentation Software 364

Smart Data Collective

APRIL 29, 2020

What is data management? Data management can be defined in many ways. Usually the term refers to the practices, techniques and tools that allow access and delivery through different fields and data structures in an organisation. Extraction, Transform, Load (ETL). Data transformation. SharePoint.

Management 98

Management Data Warehouse Digital Transformation Dashboards 98

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

JULY 25, 2024

In addition, with OpenSearch Service, you get advanced security with fine-grained access control, the ability to store and analyze log data for observability and security, along with dashboarding and alerting. You’ll have all of CloudSearch’s capabilities and more.

Cost-Benefit 126

Cost-Benefit Machine Learning Dashboards Management 126

FineReport

MARCH 7, 2024

As we explore examples of data analysis reports and interactive report data analysis dashboards, we embark on a journey to unravel the nuanced art of transforming raw data into meaningful narratives that empower decision-makers. Try FineReport Now 1. Try FineReport Now 1.1 Try FineReport Now 1.1

Dashboards 52

Dashboards Reporting Advertising Statistics 52

O'Reilly on Data

JANUARY 17, 2023

” I, thankfully, learned this early in my career, at a time when I could still refer to myself as a software developer. That takes us to a conspicuous omission from that list of roles: the data scientists who focused on building basic models. Companies will still need advanced ML modeling and data viz, sure.

Machine Learning 363

Machine Learning Predictive Modeling Software Modeling 363

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 110

Data Warehouse Analytics Testing Sales 110

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 98

Dashboards Visualization Metrics Data Transformation 98

CIO Business Intelligence

APRIL 30, 2024

This feature enables users to save calculations from a Tableau dashboard directly to Tableau’s metrics layer so they can monitor and track the information over time. Einstein Copilot for Tableau remains in beta, but Tableau announced two new features for the AI assistant as well: AI-assisted data transformation.

Analytics 96

Analytics Metrics Visualization Dashboards 96

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 119

Visualization Dashboards Data-driven Gap analysis 119

AWS Big Data

FEBRUARY 6, 2023

Amazon QuickSight dashboards showcase the results from the analyzer. For more details on how to configure and schedule the log collector, refer to the yarn-log-collector GitHub repo. For more information on how to use the YARN log organizer, refer to the yarn-log-organizer GitHub repo.

Dashboards 98

Dashboards Optimization Data Lake Cost-Benefit 98

AWS Big Data

DECEMBER 21, 2023

For setup instructions, refer to Getting started with Amazon OpenSearch Service. Choose the link under OpenSearch Dashboards URL. After the job runs successfully, navigate to OpenSearch Dashboards, and log in to the dashboard. Choose Dashboards Management on the navigation menu.

Analytics 111

Analytics IT Data Lake Visualization 111

AWS Big Data

JANUARY 27, 2023

In this post, we show you how to use PCA’s data to build automated QuickSight dashboards for advanced analytics to assist in quality assurance (QA) and quality management (QM) processes. You can apply data, agent, call duration, and language filters for targeted search. Select -PCA-Dashboard and choose Share.

Analytics 87

Analytics Reporting Dashboards Visualization 87

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 54

Data Warehouse Data Architecture Machine Learning Data Transformation 54

AWS Big Data

MARCH 3, 2023

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Let’s refer to this S3 bucket as the raw layer. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

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 94

Cost-Benefit Data Processing Optimization Data-driven 94

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. The data warehouse is highly business critical with minimal allowable downtime. For an example, refer to How JPMorgan Chase built a data mesh architecture to drive significant value to enhance their enterprise data platform.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

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 111

IoT Data Warehouse Cost-Benefit Reporting 111

AWS Big Data

AUGUST 19, 2024

This report is essential for understanding revenue streams, identifying opportunities for optimization, and making data-driven decisions regarding pricing and promotions. Refer to Enabling AWS PrivateLink in the Snowflake documentation to verify the steps, required access level, and service level to set the configurations. Choose Next.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

AWS Big Data

NOVEMBER 13, 2023

Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster. Also, over time the number of BI dashboards (both scheduled and live) increased, which contributed to more queries being submitted to the Redshift cluster.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

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 JOB_NAME All The process name from the ETL framework.

Enterprise 111

Enterprise Data Warehouse Data Lake Optimization 111

AWS Big Data

MAY 3, 2023

Components of the consumer application The consumer application comprises three main parts that work together to consume, transform, and load messages from Amazon MSK into a target database. The following diagram shows an example of data transformations in the handler component.

IoT 111

IoT Internet of Things Data Transformation Management 111

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 96

Reporting Metrics Optimization Data Lake 96

AWS Big Data

JUNE 29, 2023

Kinesis Data Analytics for Apache Flink In our example, we perform the following actions on the streaming data: Connect to an Amazon Kinesis Data Streams data stream. View the stream data. Transform and enrich the data. Manipulate the data with Python. Open the file to inspect the new data.

Data Analytics 104

Data Analytics Analytics IoT Data Lake 104

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. Enable responsible, transparent and explainable data and AI workflows with watsonx.governance.

Risk 70

Risk Modeling Management Metadata 70

FineReport

APRIL 21, 2024

In summary, embedded analytics refers to actionable intelligence seamlessly integrated into customer-facing products, applications, or services. Lengthy Turnaround Time In the competitive landscape of analytics, swift delivery of insights is paramount to proving the value of data and analytics teams.

Dashboards 52

Dashboards Visualization Interactive Business Intelligence 52

AWS Big Data

JULY 26, 2023

Plan In the planning phase, developers collect requirements from stakeholders such as end-users to define a data requirement. You can use your preferred IDE to implement AWS resource definition using the AWS Cloud Development Kit (AWS CDK) or AWS CloudFormation , and also the business logic of AWS Glue job scripts for data integration.

Data Integration 97

Data Integration Snapshot Testing Visualization 97

Jet Global

MAY 28, 2019

A data warehouse is typically used by companies with a high level of data diversity or analytical requirements. When you want to get answers from your data, your request goes directly to the appropriate cube. When organizations start to collect data in multiple databases, the size of the data sets grow exponentially.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

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. Refer to Managing Amazon Redshift Serverless using the console for setup steps. We create a datashare called prod_datashare to allow the serverless instance access to data in the provisioned cluster.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 52

AWS Big Data

FEBRUARY 6, 2023

The results of the log analyzer reveal Hadoop workload insights with various views and metrics of the Hadoop applications shown in Amazon QuickSight dashboards, which leads to the design of a future EMR cluster. The QuickSight timeline dashboard shows the peak time job runs because of the daily batch job.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

Alation

JANUARY 17, 2023

A modern data stack relies on cloud computing, whereas a legacy data stack stores data on servers instead of in the cloud. Modern data stacks provide access for more data professionals than a legacy data stack. Examples of data transformation tools include dbt and dataform.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

Sisense

MAY 11, 2021

Data teams dealing with larger, faster-moving cloud datasets needed more robust tools to perform deeper analyses and set the stage for next-level applications like machine learning and natural language processing. One solution with immense potential is ”edge computing.”

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Alation

OCTOBER 28, 2021

Protect data at the source. Put data into action to optimize the patient experience and adapt to changing business models. What is Data Governance in Healthcare? Data governance in healthcare refers to how data is collected and used by hospitals, pharmaceutical companies, and other healthcare organizations and service providers.

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

AWS Big Data

FEBRUARY 26, 2024

Additionally, you can configure OpenSearch Ingestion to apply data transformations before delivery. The content includes a reference architecture, a step-by-step guide on infrastructure setup, sample code for implementing the solution within a use case, and an AWS Cloud Development Kit (AWS CDK) application for deployment.

Dashboards 85

Dashboards Testing Metrics Optimization 85

Jet Global

MAY 1, 2023

that gathers data from many sources. Their dashboards were visually stunning. In turn, end users were thrilled with the bells and whistles of charts, graphs, and dashboards. Yes—but basic dashboards won’t be enough. These users interact with dashboards and reports as well as personalized views of the information.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52