Data Ingestion, ETL and Information - Artificial Intelligence Zone

Basil Faruqui, BMC: Why DataOps needs orchestration to make it work

AI News

AUGUST 29, 2023

If you think about building a data pipeline, whether you’re doing a simple BI project or a complex AI or machine learning project, you’ve got data ingestion, data storage and processing, and data insight – and underneath all of those four stages, there’s a variety of different technologies being used,” explains Faruqui.

Data Ingestion

Data Ingestion Big Data Explainability ETL

What is Data Ingestion? Understanding the Basics

Pickl AI

JULY 25, 2024

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making. This is where data ingestion comes in.

Data Ingestion

Data Ingestion ETL Data Quality Data Integration

A Simple Guide to Real-Time Data Ingestion

Pickl AI

JULY 24, 2023

What is Real-Time Data Ingestion? Real-time data ingestion is the practise of gathering and analysing information as it is produced, without little to no lag between the emergence of the data and its accessibility for analysis. Traders need up-to-the-second information to make informed decisions.

Data Ingestion

Data Ingestion ETL Data Integration Data Science

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ETL Process Explained: Essential Steps for Effective Data Management

Pickl AI

OCTOBER 17, 2024

Summary: The ETL process, which consists of data extraction, transformation, and loading, is vital for effective data management. Following best practices and using suitable tools enhances data integrity and quality, supporting informed decision-making. What is ETL? ETL stands for Extract, Transform, Load.

ETL

ETL Explainability Data Integration Data Extraction

How Rocket Companies modernized their data science solution on AWS

AWS Machine Learning Blog

FEBRUARY 21, 2025

Thats why we use advanced technology and data analytics to streamline every step of the homeownership experience, from application to closing. Rockets legacy data science architecture is shown in the following diagram. Data Storage and Processing: All compute is done as Spark jobs inside of a Hadoop cluster using Apache Livy and Spark.

Data Science

Data Science Data Scientist Data Ingestion DevOps

A Beginner’s Guide to Data Warehousing

Unite.AI

DECEMBER 5, 2023

In BI systems, data warehousing first converts disparate raw data into clean, organized, and integrated data, which is then used to extract actionable insights to facilitate analysis, reporting, and data-informed decision-making. The following elements serve as a backbone for a functional data warehouse.

Metadata

Metadata Big Data ETL Data Mining

Improving air quality with generative AI

AWS Machine Learning Blog

JUNE 18, 2024

Through evaluations of sensors and informed decision-making support, Afri-SET empowers governments and civil society for effective air quality management. This manual synchronization process, hindered by disparate data formats, is resource-intensive, limiting the potential for widespread data orchestration.

Generative AI

Generative AI Data Ingestion Python LLM

Build an image search engine with Amazon Kendra and Amazon Rekognition

AWS Machine Learning Blog

MAY 5, 2023

The following figure shows an example diagram that illustrates an orchestrated extract, transform, and load (ETL) architecture solution. Identifying keywords such as use cases and industry verticals in these sources also allows the information to be captured and for more relevant search results to be displayed to the user.

Metadata

Metadata ETL ML Data Ingestion

Introduction to Apache NiFi and Its Architecture

Pickl AI

JULY 30, 2024

Summary: Apache NiFi is a powerful open-source data ingestion platform design to automate data flow management between systems. Its architecture includes FlowFiles, repositories, and processors, enabling efficient data processing and transformation.

Data Ingestion

Data Ingestion ETL Big Data Data Integration

Build a news recommender application with Amazon Personalize

AWS Machine Learning Blog

APRIL 4, 2024

Tackling these challenges is key to effectively connecting readers with content they find informative and engaging. AWS Glue performs extract, transform, and load (ETL) operations to align the data with the Amazon Personalize datasets schema. The following diagram illustrates the data ingestion architecture.

ETL

ETL Auto-complete Metadata Data Ingestion

Leveraging Data Engineering to Enhance Customer 360 Initiatives

TransOrg Analytics

AUGUST 21, 2024

Customer 360 initiatives are designed to bring together relevant information about individual consumers from different touch points, including but not limited to sales, marketing, customer service, and social media platforms. How Data Engineering Enhances Customer 360 Initiatives 1.

Big Data Engineer

Big Data Engineer ETL Data Ingestion Data Integration

Unfolding the Details of Hive in Hadoop

Pickl AI

JULY 6, 2023

These work together to enable efficient data processing and analysis: · Hive Metastore It is a central repository that stores metadata about Hive’s tables, partitions, and schemas. Thus, making it easier for analysts and data scientists to leverage their SQL skills for Big Data analysis.

Big Data

Big Data Data Analysis ETL Metadata

Build Data Pipelines: Comprehensive Step-by-Step Guide

Pickl AI

JULY 8, 2024

It covers best practices for ensuring scalability, reliability, and performance while addressing common challenges, enabling businesses to transform raw data into valuable, actionable insights for informed decision-making. As stated above, data pipelines represent the backbone of modern data architecture.

Data Quality

Data Quality ETL Data Integration Automation

Unlocking the 12 Ways to Improve Data Quality

Pickl AI

OCTOBER 19, 2023

Hence, the quality of data is significant here. Quality data fuels business decisions, informs scientific research, drives technological innovations, and shapes our understanding of the world. The Relevance of Data Quality Data quality refers to the accuracy, completeness, consistency, and reliability of data.

Data Quality

Data Quality ETL Machine Learning Data Ingestion

Supercharging Your Data Pipeline with Apache Airflow (Part 2)

Heartbeat

NOVEMBER 6, 2023

Image Source — Pixel Production Inc In the previous article, you were introduced to the intricacies of data pipelines, including the two major types of existing data pipelines. You also learned how to build an Extract Transform Load (ETL) pipeline and discovered the automation capabilities of Apache Airflow for ETL pipelines.

ETL

ETL Python Metadata Deep Learning

Popular Data Transformation Tools: Importance and Best Practices

Pickl AI

OCTOBER 10, 2024

Apache Nifi Apache Nifi is an open-source data integration tool that automates system data flow. Its drag-and-drop interface makes it user-friendly, allowing data engineers to build complex workflows without extensive coding knowledge. AWS Glue AWS Glue is a fully managed ETL service provided by Amazon Web Services.

ETL

ETL Data Quality Machine Learning Business Intelligence

Comparing Tools For Data Processing Pipelines

The MLOps Blog

MARCH 15, 2023

This is what data processing pipelines do for you. Automating myriad steps associated with pipeline data processing, helps you convert the data from its raw shape and format to a meaningful set of information that is used to drive business decisions.

ETL

ETL Categorization Data Integration Automation

Differentiation: Microsoft Fabric vs Power BI

Pickl AI

DECEMBER 16, 2024

Its core components include: Lakehouse : Offers robust data storage and processing capabilities. Data Factory : Simplifies the creation of ETL pipelines to integrate data from diverse sources. It supports a broad range of data types and sources, ensuring robust data management across silos.

ETL

ETL Data Ingestion Data Integration Machine Learning

How to Build Machine Learning Systems With a Feature Store

The MLOps Blog

JANUARY 26, 2024

Recommended How to Solve the Data Ingestion and Feature Store Component of the MLOps Stack Read more A unified architecture for ML systems One of the challenges in building machine-learning systems is architecting the system. These features are computed on-demand using feature functions.

Machine Learning

Machine Learning Metadata ML Python

Building an efficient MLOps platform with OSS tools on Amazon ECS with AWS Fargate

AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. For more information, see Zeta Global’s home page. Every Airflow task calls Amazon ECS tasks with some overrides.

Machine Learning

Machine Learning Data Scientist ML Data Ingestion

TransOrg’s Cloud Data Engineering Services on AWS, GCP & Snowflake

TransOrg Analytics

SEPTEMBER 24, 2024

Data Foundation on AWS Amazon S3: Scalable storage foundation for data lakes. AWS Lake Formation: Simplify the process of creating and managing a secure data lake. Amazon Redshift: Fast, scalable data warehouse for analytics. AWS Glue: Fully managed ETL service for easy data preparation and integration.

ETL

ETL LLM Data Ingestion Automation

TransOrg’s Cloud Data Engineering Services on AWS, GCP & Snowflake

TransOrg Analytics

SEPTEMBER 24, 2024

Data Foundation on AWS Amazon S3: Scalable storage foundation for data lakes. AWS Lake Formation: Simplify the process of creating and managing a secure data lake. Amazon Redshift: Fast, scalable data warehouse for analytics. AWS Glue: Fully managed ETL service for easy data preparation and integration.

ETL

ETL LLM Data Ingestion Automation

Driving Progress with Open Data Science: Trends, Tools, and Opportunities

ODSC - Open Data Science

DECEMBER 9, 2024

Instead, flexible open-source programming languages and public data repositories are empowering anyone to experiment, build models, and question through data. Students, academics, startupsall levels now avail equal resources to mine information forgood. In fact, statistics show the expansion firsthand.

Data Science

Data Science Data Scientist Python Machine Learning

Artificial Intelligence Zone

Basil Faruqui, BMC: Why DataOps needs orchestration to make it work

What is Data Ingestion? Understanding the Basics

Webinars

Trending Sources

A Simple Guide to Real-Time Data Ingestion

Webinars

ETL Process Explained: Essential Steps for Effective Data Management

How Rocket Companies modernized their data science solution on AWS

A Beginner’s Guide to Data Warehousing

Improving air quality with generative AI

Build an image search engine with Amazon Kendra and Amazon Rekognition

Introduction to Apache NiFi and Its Architecture

Build a news recommender application with Amazon Personalize

Leveraging Data Engineering to Enhance Customer 360 Initiatives

Unfolding the Details of Hive in Hadoop

Build Data Pipelines: Comprehensive Step-by-Step Guide

Unlocking the 12 Ways to Improve Data Quality

Supercharging Your Data Pipeline with Apache Airflow (Part 2)

Popular Data Transformation Tools: Importance and Best Practices

Comparing Tools For Data Processing Pipelines

Differentiation: Microsoft Fabric vs Power BI

How to Build Machine Learning Systems With a Feature Store

Building an efficient MLOps platform with OSS tools on Amazon ECS with AWS Fargate

TransOrg’s Cloud Data Engineering Services on AWS, GCP & Snowflake

TransOrg’s Cloud Data Engineering Services on AWS, GCP & Snowflake

Driving Progress with Open Data Science: Trends, Tools, and Opportunities

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