AI News

SEPTEMBER 29, 2024

Ahead of AI & Big Data Expo Europe , Han Heloir, EMEA gen AI senior solutions architect at MongoDB , discusses the future of AI-powered applications and the role of scalable databases in supporting generative AI and enhancing business processes. Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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Big Data ETL Generative AI Data Ingestion 232

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.

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Data Ingestion Explainability Big Data ETL 169

Pickl AI

OCTOBER 10, 2024

Summary: Data transformation tools streamline data processing by automating the conversion of raw data into usable formats. These tools enhance efficiency, improve data quality, and support Advanced Analytics like Machine Learning. These tools automate the process, making it faster and more accurate.

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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. What is Apache NiFi?

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Unite.AI

SEPTEMBER 22, 2023

Data warehousing has evolved quite a bit in the past 20-25 years. There are a lot of repetitive tasks and automation's goal is to help users in front of repetition. We already know patterns- the patterns have been around for such a long time and the patterns are repetitive. Why is Astera a superior solution than competing platforms?

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Large Language Models Automation Artificial Intelligence Artificial Intelligence 278

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.

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ODSC - Open Data Science

OCTOBER 18, 2024

The advent of big data, affordable computing power, and advanced machine learning algorithms has fueled explosive growth in data science across industries. However, research shows that up to 85% of data science projects fail to move beyond proofs of concept to full-scale deployment.

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Data Science ETL Data Scientist Data Quality 52

Pickl AI

NOVEMBER 4, 2024

Introduction Data Engineering is the backbone of the data-driven world, transforming raw data into actionable insights. As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. ETL is vital for ensuring data quality and integrity.

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Data Quality ETL Data Integration Machine Learning 52

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.

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Big Data Metadata ETL Business Intelligence 98

ODSC - Open Data Science

OCTOBER 9, 2024

By automating repetitive tasks and generating boilerplate code, these tools free up time for engineers to focus on more complex, creative aspects of software development. Well, it is offering a way to automate the time-consuming process of writing and running tests. Just keep in mind, that this shouldn’t replace the human element.

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Software Engineer Software Development DevOps ETL 40

AWS Machine Learning Blog

NOVEMBER 12, 2024

Led by agricultural technology innovators, generative AI is the latest AI technology that helps agronomists and researchers have open-ended human-like interactions with computing applications to assist with a variety of tasks and automate historically manual processes. Agmatix’s technology architecture is built on AWS.

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Generative AI Prompt Engineering Prompt Engineer AI 101

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.

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Data Science ETL Big Data Deep Learning 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. It has a quick and clear grasp of data quality issues.

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Data Quality Metadata Data Integration ETL 115

Artificial Corner

JUNE 6, 2023

Timeline of data engineering — Created by the author using canva In this post, I will cover everything from the early days of data storage and relational databases to the emergence of big data, NoSQL databases, and distributed computing frameworks. MongoDB, developed by MongoDB Inc.,

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Data Mining Big Data ETL Machine Learning 52

The MLOps Blog

MARCH 15, 2023

As the volume of data keeps increasing at an accelerated rate, these data tasks become arduous in no time leading to an extensive need for automation. This is what data processing pipelines do for you. Let’s understand how the other aspects of a data pipeline help the organization achieve its various objectives.

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Marktechpost

JULY 23, 2023

The pay-per-use cloud-based data warehousing technologies are quick, effective, and highly scalable. Importance of Data Warehouse To meet the continuously shifting needs of business, modern data warehousing solutions automate the repetitive tasks of designing, developing, and putting in place a data warehouse architecture.

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Machine Learning ETL Big Data Data Integration 52

TransOrg Analytics

AUGUST 21, 2024

Such success stories have largely depended on Data Engineering processes. This article explores how data engineering can improve Customer 360 initiatives for AWS data engineering , big data engineering, and data analytics companies. Data Storage: Keeping altered data within Azure Synapse’s enrichment layer.

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ETL Big Data Engineer Data Ingestion Data Integration 52

Mlearning.ai

JULY 10, 2023

[link] Tables The table in GCP BigQuery is a collection of rows and columns that can store and manage massive amounts of data. It’s a managed, cloud-based service that’s designed to handle big data processing with ease. You can use stored procedures to handle complex ETL processes, make API calls, and perform data validation.

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Data Science Big Data ETL Automation 52

Marktechpost

JULY 17, 2023

Data gathering, pre-processing, modeling, and deployment are all steps in the iterative process of predictive analytics that results in output. We can automate the procedure to deliver forecasts based on new data continuously fed throughout time. This tool’s user-friendly UI consistently receives acclaim from users.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

For instance, a notebook that monitors for model data drift should have a pre-step that allows extract, transform, and load (ETL) and processing of new data and a post-step of model refresh and training in case a significant drift is noticed.

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AWS Machine Learning Blog

SEPTEMBER 6, 2024

Experimenting with LLMs to automate fact generation from QA ground truth using LLMs can help. Automate, but verify, with LLMs – Use LLMs to generate initial ground truth answers and facts, with a human review and curation to align with the desired assistant output standards.

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Flipboard

NOVEMBER 22, 2024

This is a new capability that enables data engineers and scientists to quickly identify and resolve issues in their Spark applications. This feature uses ML and generative AI technologies to provide automated root cause analysis for failed Spark applications, along with actionable recommendations and remediation steps. Choose your job.

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Generative AI Software Development ETL Big Data Architect 144

Flipboard

NOVEMBER 24, 2023

This emergent ability in LLMs has compelled software developers to use LLMs as an automation and UX enhancement tool that transforms natural language to a domain-specific language (DSL): system instructions, API requests, code artifacts, and more. We use the following prompt: Human: Your job is to act as an expert on ETL pipelines.

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Pickl AI

JULY 18, 2024

In contrast, MongoDB uses a more straightforward query language that works well with JSON data structures. MongoDB’s horizontal scaling capabilities surpass relational databases’ typical vertical scaling limitations, making it suitable for big data applications. What Is a MongoDB Atlas?

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Explainability ETL Data Science Python 52

Pickl AI

JUNE 11, 2024

Let’s delve into the key components that form the backbone of a data warehouse: Source Systems These are the operational databases, CRM systems, and other applications that generate the raw data feeding the data warehouse. Data Extraction, Transformation, and Loading (ETL) This is the workhorse of architecture.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

Architecture overview Our MLOps architecture is designed to automate and monitor all stages of the ML lifecycle. An example direct acyclic graph (DAG) might automate data ingestion, processing, model training, and deployment tasks, ensuring that each step is run in the correct order and at the right time.

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Machine Learning Data Scientist Data Ingestion ML 108

TransOrg Analytics

SEPTEMBER 24, 2024

Our cloud data engineering services are designed to transform your business by creating robust and scalable data foundations across any scale. We provide comprehensive solutions to assess, architect, build, deploy, and automate your data engineering landscape on the leading cloud platforms.

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AWS Machine Learning Blog

AUGUST 2, 2024

About the authors Vicente Cruz Mínguez is the Head of Data & Advanced Analytics at Cepsa Química. He has more than 8 years of experience with big data and machine learning projects in financial, retail, energy, and chemical industries. The following diagram illustrates this architecture.

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