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 76

Risk Modeling Management Metadata 76

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

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 72

Reporting Metrics Optimization Data Lake 72

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 75

Data Integration Snapshot Testing Visualization 75

AWS Big Data

OCTOBER 11, 2023

Key performance indicators (KPIs) of interest for a call center from a near-real-time platform could be calls waiting in the queue, highlighted in a performance dashboard within a few seconds of data ingestion from call center streams. Visualize KPIs of call center performance in near-real time through OpenSearch Dashboards.

Management 112

Management Metadata Analytics Dashboards 112

AWS Big Data

NOVEMBER 15, 2023

The CLEA dashboards were built on the foundation of the Well-Architected Lab. For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. Data providers and consumers are the two fundamental users of a CDH dataset.

Dashboards 101

Dashboards Analytics Metadata Data Warehouse 101

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

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 88

Dashboards Visualization Metrics Data Transformation 88

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 104

Visualization Dashboards Data-driven Gap analysis 104

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 98

Data Warehouse Data Lake Analytics Data Science 98

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 86

Data Lake Dashboards Metrics Metadata 86

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 79

Data Analytics Analytics IoT Data Lake 79

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 Transformation Data Science 52

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 108

IoT Internet of Things Data Transformation Management 108

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 325

Machine Learning Predictive Modeling Software Modeling 325

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 91

Enterprise Data Warehouse Data Lake Optimization 91

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 346

IT Testing Experimentation Software 346

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 Metrics Modeling 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

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 69

Cost-Benefit Data Processing Optimization Data-driven 69

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

CIO Business Intelligence

JANUARY 24, 2024

Gather/Insert data on market trends, customer behavior, inventory levels, or operational efficiency. IoT, Web Scraping, API, IDP, RPA Data Processing Data Pipelines and Analysis Layer Employ data pipelines with algorithms to filter, sort, and interpret data, transforming raw information into actionable insights.

IoT 118

IoT Machine Learning Optimization Internet of Things 118

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

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 Sales 52