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 99

Analytics IT Data Lake Visualization 99

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 87

Dashboards Visualization Metrics Data Transformation 87

AWS Big Data

JANUARY 27, 2023

You can visualize the PCA insights in the business intelligence (BI) tool Amazon QuickSight for advanced analysis. 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.

Analytics 62

Analytics Reporting Dashboards Visualization 62

AWS Big Data

FEBRUARY 6, 2023

In this post, we dive deep into the tool, walking through all steps from log ingestion, transformation, visualization, and architecture design to calculate TCO. Amazon QuickSight dashboards showcase the results from the analyzer. This step creates datasets on QuickSight dashboards in your AWS target account.

Dashboards 78

Dashboards Optimization Data Lake Cost-Benefit 78

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 65

Dashboards Testing Metrics Optimization 65

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

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 mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

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 85

Data Lake Dashboards Metrics Metadata 85

Jet Global

MAY 1, 2023

that gathers data from many sources. We rely on increasingly mobile technology to comb through massive amounts of data and solve high-value problems. Plus, there is an expectation that tools be visually appealing to boot. In the past, data visualizations were a powerful way to differentiate a software application.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 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 74

Data Integration Snapshot Testing Visualization 74

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 99

IoT Machine Learning Optimization Internet of Things 99

AWS Big Data

JUNE 29, 2023

Notebooks are provisioned quickly and provide a way for you to instantly view and analyze your streaming data. This pipeline could further be used to send data to Amazon OpenSearch Service or other targets for additional processing and visualization. View the stream data. Transform and enrich the data.

Data Analytics 77

Data Analytics Analytics IoT Data Lake 77

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

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. Business Intelligence Tools: Business intelligence (BI) tools are used to visualize your data.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 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 325

Machine Learning Predictive Modeling Software Modeling 325