ODSC - Open Data Science

JUNE 19, 2023

With the advent of big data in the modern world, RTOS is becoming increasingly important. As software expert Tim Mangan explains, a purpose-built real-time OS is more suitable for apps that involve tons of data processing. The Big Data and RTOS connection IoT and embedded devices are among the biggest sources of big data.

Big Data 96

Big Data ETL Data Science Artificial Intelligence 96

AI News

SEPTEMBER 26, 2023

Our composable CDP ensures your data is AI-ready, helping you collect, clean, and activate customer data with our open, API-first platform and 450+ pre-built connectors that enable you to start with data anywhere and activate it everywhere. HT: Twilio Segment is excited to be taking part in AI & Big Data Expo Europe in 2023!

Big Data 319

Big Data AI AI ETL 319

Flipboard

NOVEMBER 7, 2023

“Data is at the center of every application, process, and business decision,” wrote Swami Sivasubramanian, VP of Database, Analytics, and Machine Learning at AWS, and I couldn’t agree more. A common pattern customers use today is to build data pipelines to move data from Amazon Aurora to Amazon Redshift.

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ETL Machine Learning Big Data 181

AI News

AUGUST 29, 2023

Apart from the time-sensitive necessity of running a business with perishable, delicate goods, the company has significantly adopted Azure, moving some existing ETL applications to the cloud, while Hershey’s operations are built on a complex SAP environment. Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

Data Ingestion 231

Data Ingestion Big Data Explainability ETL 231

Marktechpost

JUNE 13, 2024

ELT Pipelines: Typically used for big data, these pipelines extract data, load it into data warehouses or lakes, and then transform it. It is suitable for distributed and scalable large-scale data processing, providing quick big-data query and analysis capabilities.

ETL 128

ETL Machine Learning Data Ingestion Big Data 128

Marktechpost

APRIL 1, 2024

Existing research emphasizes the significance of distributed processing and data quality control for enhancing LLMs. Utilizing frameworks like Slurm and Spark enables efficient big data management, while data quality improvements through deduplication, decontamination, and sentence length adjustments refine training datasets.

Large Language Models 113

Large Language Models ETL Data Ingestion Data Quality 113

AWS Machine Learning Blog

NOVEMBER 20, 2024

She has experience across analytics, big data, ETL, cloud operations, and cloud infrastructure management. Data Engineer at Amazon Ads. He builds and manages data-driven solutions for recommendation systems, working together with a diverse and talented team of scientists, engineers, and product managers.

ETL 111

ETL IDP Big Data Generative AI 111

Unite.AI

SEPTEMBER 16, 2024

It offers both open-source and enterprise/paid versions and facilitates big data management. Key Features: Seamless integration with cloud and on-premise environments, extensive data quality, and governance tools. Pros: Scalable, strong data governance features, support for big data.

Data Integration 173

Data Integration ETL Big Data Automation 173

AWS Machine Learning Blog

FEBRUARY 18, 2025

To handle the log data efficiently, raw logs were centralized into an Amazon Simple Storage Service (Amazon S3) bucket. An Amazon EventBridge schedule checked this bucket hourly for new files and triggered log transformation extract, transform, and load (ETL) pipelines built using AWS Glue and Apache Spark.

Generative AI 70

Generative AI ETL LLM AI 70

Unite.AI

SEPTEMBER 16, 2024

It offers both open-source and enterprise/paid versions and facilitates big data management. Key Features: Seamless integration with cloud and on-premise environments, extensive data quality, and governance tools. Pros: Scalable, strong data governance features, support for big data.

Data Integration 173

Data Integration ETL Big Data Automation 173

Pickl AI

OCTOBER 6, 2024

Summary: This blog explores the key differences between ETL and ELT, detailing their processes, advantages, and disadvantages. Understanding these methods helps organizations optimize their data workflows for better decision-making. What is ETL? ETL stands for Extract, Transform, and Load.

ETL 52

ETL Data Quality Data Integration Big Data 52

Marktechpost

JULY 18, 2023

Extract, Transform, and Load are referred to as ETL. ETL is the process of gathering data from numerous sources, standardizing it, and then transferring it to a central database, data lake, data warehouse, or data store for additional analysis. Involved in each step of the end-to-end ETL process are: 1.

ETL 52

ETL Data Integration Business Intelligence Automation 52

Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

Big Data 52

Big Data Machine Learning Algorithm Data Scientist 52

Unite.AI

DECEMBER 5, 2023

In this digital economy, data is paramount. Today, all sectors, from private enterprises to public entities, use big data to make critical business decisions. However, the data ecosystem faces numerous challenges regarding large data volume, variety, and velocity. Enter data warehousing!

Metadata 162

Metadata Big Data ETL Data Mining 162

Pickl AI

MARCH 19, 2025

It is ideal for handling unstructured or semi-structured data, making it perfect for modern applications that require scalability and fast access. Apache Spark Apache Spark is a powerful data processing framework that efficiently handles Big Data. It integrates well with various data sources, making analysis easier.

Big Data 52

Big Data Automation Data Science Python 52

Pickl AI

JANUARY 27, 2025

Summary: HDFS in Big Data uses distributed storage and replication to manage massive datasets efficiently. By co-locating data and computations, HDFS delivers high throughput, enabling advanced analytics and driving data-driven insights across various industries. It fosters reliability. between 2024 and 2030.

Big Data 52

Big Data Data Integration ETL Metadata 52

Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Choosing the right ETL tool is crucial for smooth data management.

ETL 40

ETL Data Integration Data Quality Metadata 40

Unite.AI

SEPTEMBER 22, 2023

Automation has been a key trend in the past few years and that ranges from the design to building of a data warehouse to loading and maintaining, all of that can be automated.

Large Language Models 278

Large Language Models Automation Artificial Intelligence Artificial Intelligence 278

Flipboard

JUNE 26, 2023

Transform raw insurance data into CSV format acceptable to Neptune Bulk Loader , using an AWS Glue extract, transform, and load (ETL) job. When the data is in CSV format, use an Amazon SageMaker Jupyter notebook to run a PySpark script to load the raw data into Neptune and visualize it in a Jupyter notebook.

Auto-complete 123

Auto-complete ML Auto-classification ETL 123

Becoming Human

JANUARY 23, 2023

Nowadays most businesses use data science, whether a business is product-based or service-based they use data science for their growth. Data Science and Big Data There is an Umbrella of Big data and what is Big Data?

Data Science 105

Data Science Big Data Data Mining Deep Learning 105

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 130

Data Quality Metadata ETL Big Data 130

AWS Machine Learning Blog

FEBRUARY 21, 2025

Previously, he was a Data & Machine Learning Engineer at AWS, where he worked closely with customers to develop enterprise-scale data infrastructure, including data lakes, analytics dashboards, and ETL pipelines.

LLM 120

LLM Large Language Models Natural Language Processing Machine Learning 120

Flipboard

DECEMBER 11, 2024

About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. Chiho Sugimoto is a Cloud Support Engineer on the AWS Big Data Support team. She is passionate about helping customers build data lakes using ETL workloads. Big Data Architect. Zach Mitchell is a Sr.

Big Data Architect 160

Big Data Architect Big Data ML Generative AI 160

AWS Machine Learning Blog

FEBRUARY 2, 2024

The embeddings are captured in Amazon Simple Storage Service (Amazon S3) via Amazon Kinesis Data Firehose , and we run a combination of AWS Glue extract, transform, and load (ETL) jobs and Jupyter notebooks to perform the embedding analysis. Set the parameters for the ETL job as follows and run the job: Set --job_type to BASELINE.

ETL 120

ETL DevOps LLM Generative AI 120

Towards AI

APRIL 3, 2024

The ORC and Parquet are columnal storage and they are famous in the Big Data world because of their efficient storage. Create a new Glue Crawler to discover and catalog your data in S3. This is necessary for Glue to understand the structure of your data. Create a Glue Job to perform ETL operations on your data.

ETL 105

ETL Big Data AI AI 105

ODSC - Open Data Science

SEPTEMBER 27, 2023

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. Unlike traditional data warehouses or relational databases, data lakes accept data from a variety of sources, without the need for prior data transformation or schema definition.

Big Data 98

Big Data Metadata ETL Data Science 98

Analytics Vidhya

FEBRUARY 27, 2023

Introduction Enterprises here and now catalyze vast quantities of data, which can be a high-end source of business intelligence and insight when used appropriately. Delta Lake allows businesses to access and break new data down in real time.

Business Intelligence 315

Business Intelligence ETL Big Data 315

Pickl AI

JULY 30, 2024

Its architecture includes FlowFiles, repositories, and processors, enabling efficient data processing and transformation. With a user-friendly interface and robust features, NiFi simplifies complex data workflows and enhances real-time data integration. Its visual interface allows users to design complex ETL workflows with ease.

Data Ingestion 52

Data Ingestion ETL Big Data Data Integration 52

Marktechpost

JUNE 5, 2024

You may use OpenRefine for more than just data cleaning; it can also help you find mistakes and outliers that could compromise your data’s quality. Apache Griffin Apache Griffin is an open-source data quality tool that aims to enhance big data processes.

Data Quality 113

Data Quality Metadata Data Integration ETL 113

Pickl AI

SEPTEMBER 19, 2024

It discusses performance, use cases, and cost, helping you choose the best framework for your big data needs. Introduction Apache Spark and Hadoop are potent frameworks for big data processing and distributed computing. Apache Spark is an open-source, unified analytics engine for large-scale data processing.

Big Data 52

Big Data ETL Machine Learning Python 52

Mlearning.ai

MAY 16, 2023

There are various architectural design patterns in data engineering that are used to solve different data-related problems. This article discusses five commonly used architectural design patterns in data engineering and their use cases. Finally, the transformed data is loaded into the target system.

Explainability 52

Explainability ETL Big Data Machine Learning 52

Pickl AI

OCTOBER 10, 2024

Enhanced Data Quality : These tools ensure data consistency and accuracy, eliminating errors often occurring during manual transformation. Scalability : Whether handling small datasets or processing big data, transformation tools can easily scale to accommodate growing data volumes.

ETL 52

ETL Data Quality Machine Learning Business Intelligence 52

Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Science 52

Data Science Data Scientist ETL Machine Learning 52

ODSC - Open Data Science

APRIL 3, 2023

Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis. Competence in data quality, databases, and ETL (Extract, Transform, Load) are essential.

Data Science 52

Data Science Big Data ETL Deep Learning 52

Pickl AI

JULY 6, 2023

Thus, making it easier for analysts and data scientists to leverage their SQL skills for Big Data analysis. It applies the data structure during querying rather than data ingestion. This integration allows users to combine the strengths of different tools and frameworks to solve complex big-data challenges.

Big Data 52

Big Data Data Analysis ETL Metadata 52

Marktechpost

AUGUST 27, 2024

This article lists the top data analysis courses that can help you build the essential skills needed to excel in this rapidly growing field. Introduction to Data Analytics This course provides a comprehensive introduction to data analysis, covering the roles of data professionals, data ecosystems, and Big Data tools like Hadoop and Spark.

Data Analysis 57

Data Analysis Python Data Scientist ETL 57

TransOrg Analytics

AUGUST 9, 2024

Data Quality: Without proper governance, data quality can become an issue. Performance: Query performance can be slower compared to optimized data stores. Business Applications: Big Data Analytics : Supporting advanced analytics, machine learning, and artificial intelligence applications.

Machine Learning 52

Machine Learning ETL Big Data Data Quality 52