Towards AI

JULY 1, 2024

In this article, we will look at some data engineering basics for developing a so-called ETL pipeline. For example, recently, I started working on developing a model in an open-science manner for the European Space Agency for fine-tuning an LLM on data concerning earth observation and earth science.

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IBM Journey to AI blog

MAY 15, 2024

Two of the more popular methods, extract, transform, load (ETL ) and extract, load, transform (ELT) , are both highly performant and scalable. ETL/ELT tools typically have two components: a design time (to design data integration jobs) and a runtime (to execute data integration jobs).

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Pickl AI

OCTOBER 17, 2024

Summary: This article explores the significance of ETL Data in Data Management. It highlights key components of the ETL process, best practices for efficiency, and future trends like AI integration and real-time processing, ensuring organisations can leverage their data effectively for strategic decision-making.

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Pickl AI

OCTOBER 15, 2024

Summary: Selecting the right ETL platform is vital for efficient data integration. Introduction In today’s data-driven world, businesses rely heavily on ETL platforms to streamline data integration processes. What is ETL in Data Integration? Let’s explore some real-world applications of ETL in different sectors.

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Pickl AI

OCTOBER 17, 2024

Summary: The ETL process, which consists of data extraction, transformation, and loading, is vital for effective data management. Introduction The ETL process is crucial in modern data management. What is ETL? ETL stands for Extract, Transform, Load.

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Flipboard

DECEMBER 18, 2023

He highlights innovations in data, infrastructure, and artificial intelligence and machine learning that are helping AWS customers achieve their goals faster, mine untapped potential, and create a better future. Learn more about the AWS zero-ETL future with newly launched AWS databases integrations with Amazon Redshift.

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ODSC - Open Data Science

FEBRUARY 19, 2025

In the world of AI-driven data workflows, Brij Kishore Pandey, a Principal Engineer at ADP and a respected LinkedIn influencer, is at the forefront of integrating multi-agent systems with Generative AI for ETL pipeline orchestration. ETL ProcessBasics So what exactly is ETL? filling missing values with AI predictions).

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Precisely

JANUARY 9, 2025

Artificial Intelligence (AI) is all the rage, and rightly so. The ETL (extract, transform, and load) technology market also boomed as the means of accessing and moving that data, with the necessary translations and mappings required to get the data out of source schemas and into the new DW target schema.

Data Warehouse 119

Data Warehouse Hadoop Data Governance Data Lakes 119

Smart Data Collective

AUGUST 28, 2021

Since data warehouses can deal only with structured data, they also require extract, transform, and load (ETL) processes to transform the raw data into a target structure ( Schema on Write ) before storing it in the warehouse. Therefore, ETL processes are usually required to be built around the data warehouse.

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Data Lakes Data Warehouse ETL Data Scientist 140

Smart Data Collective

OCTOBER 20, 2021

In this new reality, leveraging processes like ETL (Extract, Transform, Load) or API (Application Programming Interface) alone to handle the data deluge is not enough. The role of Artificial Intelligence and Machine Learning comes into play here. along with traditional ones challenge old models of data integration.

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Flipboard

NOVEMBER 24, 2023

SnapLogic’s AI journey In the realm of integration platforms, SnapLogic has consistently been at the forefront, harnessing the transformative power of artificial intelligence. Let’s combine these suggestions to improve upon our original prompt: Human: Your job is to act as an expert on ETL pipelines.

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Database AWS ETL SQL 159

Data Science Dojo

FEBRUARY 20, 2023

It is used by businesses across industries for a wide range of applications, including fraud prevention, marketing automation, customer service, artificial intelligence (AI), chatbots, virtual assistants, and recommendations. It focuses on two aspects of data management: ETL (extract-transform-load) and data lifecycle management.

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Machine Learning Machine Learning AWS Azure 195

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. Run an AWS Glue ETL job to merge the raw property and auto insurance data into one dataset and catalog the merged dataset. Under Data classification tools, choose Record Matching.

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Data Science Dojo

MARCH 1, 2024

As we delve into the arena of artificial intelligence, two tools emerge as pivotal enablers: LLamaIndex and LangChain. At times, the LLM responses amaze you, as they are more prompt and accurate than humans. This demonstrates their significant impact on the technology landscape today.

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Mlearning.ai

FEBRUARY 26, 2023

Which Approach is Right for Your Business? Continue reading on MLearning.ai »

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AWS Machine Learning Blog

JUNE 18, 2024

More than 170 tech teams used the latest cloud, machine learning and artificial intelligence technologies to build 33 solutions. The solution addressed in this blog solves Afri-SET’s challenge and was ranked as the top 3 winning solutions.

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IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. Db2 Warehouse fully supports open formats such as Parquet, Avro, ORC and Iceberg table format to share data and extract new insights across teams without duplication or additional extract, transform, load (ETL).

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IBM Journey to AI blog

OCTOBER 22, 2024

Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement. Data is the differentiator as business leaders look to utilize their competitive edge as they implement generative AI (gen AI).

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Data refinement: Raw data is refined into consumable layers (raw, processed, conformed, and analytical) using a combination of AWS Glue extract, transform, and load (ETL) jobs and EMR jobs. The solution consists of the following components: Data ingestion: Data is ingested into the data account from on-premises and external sources.

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Data Science AWS Hadoop Data Scientist 90

Data Science Dojo

JULY 3, 2024

Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing. Artificial Intelligence : Concepts of AI include neural networks, natural language processing (NLP), and reinforcement learning.

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Data Science Machine Learning Machine Learning Data Visualization 150

Becoming Human

JANUARY 23, 2023

So, we know that data science is a process of getting insights from data and helps the business but where this Artificial Intelligence (AI) lies? After understanding data science let’s discuss the second concern “ Data Science vs AI ”.

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ODSC - Open Data Science

APRIL 23, 2025

Credits can be used to run Python functions in the cloud without infrastructure management, ideal for ETL jobs, ML inference, or batch processing. Modal Modal offers serverless compute tailored for data-intensive workloads.

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Data Scientist Azure Apache Kafka ML 52

ODSC - Open Data Science

JUNE 19, 2023

With edge computing and generative artificial intelligence now becoming a part of modern digital life, big data is set to grow even bigger, and it is important to have a reliable embedded OS to match this growth. It is the dominant OS used in IoT and embedded systems. How does RTOS help advance big data processing?

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Big Data Big Data Artificial Intelligence Artificial Intelligence 96

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. Though it’s worth mentioning that Airflow isn’t used at runtime as is usual for extract, transform, and load (ETL) tasks.

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AWS Machine Learning Blog

JANUARY 17, 2024

To obtain such insights, the incoming raw data goes through an extract, transform, and load (ETL) process to identify activities or engagements from the continuous stream of device location pings. As part of the initial ETL, this raw data can be loaded onto tables using AWS Glue.

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Clustering AWS ML ML 136

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. He specializes in building scalable machine learning infrastructure, distributed systems, and containerization technologies.

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Precisely

FEBRUARY 20, 2025

Artificial intelligence (AI): its the ultimate example of garbage in/garbage out technology. Factors to consider include: Techniques: Choose methods like ETL (extract-transform-load), ELT (extract-load-transform), CDC (change data capture), or data virtualization.

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Data Silos AI AI Data Quality 69

ODSC - Open Data Science

AUGUST 15, 2023

For those new around here: our platform, Flow, is in effect a real-time ETL tool, but it’s also a real-time data lake with transactional support. In a nutshell, that’s what makes Flow’s approach different — both in the world of ETL and data lakes. When we built Flow, we didn’t use any of the aforementioned data lake formats.

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Data Lakes ETL Data Science Algorithm 98

Pickl AI

JUNE 11, 2024

Data Extraction, Transformation, and Loading (ETL) This is the workhorse of architecture. ETL tools act like skilled miners , extracting data from various source systems. Data warehouses act as data custodians, employing robust cleansing techniques during the ETL process.

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AWS Machine Learning Blog

JUNE 25, 2024

Amazon Bedrock , a fully managed service designed to facilitate the integration of LLMs into enterprise applications, offers a choice of high-performing LLMs from leading artificial intelligence (AI) companies like Anthropic, Mistral AI, Meta, and Amazon through a single API.

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AWS Machine Learning Blog

AUGUST 4, 2023

It eliminates tedious, costly, and error-prone ETL (extract, transform, and load) jobs. AWS and Salesforce are excited to partner together to deliver this experience to our joint customers to help them drive business processes using the power of ML and artificial intelligence.

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AWS ML ML Data Scientist 98

Alation

JANUARY 17, 2023

Reverse ETL tools. Business intelligence (BI) platforms. The modern data stack is also the consequence of a shift in analysis workflow, fromextract, transform, load (ETL) to extract, load, transform (ELT). A Note on the Shift from ETL to ELT. In the past, data movement was defined by ETL: extract, transform, and load.

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Data Warehouse ETL Tableau Cloud Data 52

AWS Machine Learning Blog

AUGUST 2, 2024

Generative artificial intelligence (AI) is rapidly emerging as a transformative force, poised to disrupt and reshape businesses of all sizes and across industries. This is a guest post co-written with Vicente Cruz Mínguez, Head of Data and Advanced Analytics at Cepsa Química, and Marcos Fernández Díaz, Senior Data Scientist at Keepler.

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IBM Journey to AI blog

MAY 20, 2024

Implement data lineage tooling and methodologies: Tools are available that help organizations track the lineage of their data sets from ultimate source to target by parsing code, ETL (extract, transform, load) solutions and more.

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Machine Learning Machine Learning Data Scientist ML 110

ODSC - Open Data Science

JUNE 12, 2023

Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts.

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Pickl AI

NOVEMBER 4, 2024

ETL Processes In Extract, Transform, Load (ETL) operations, ODBC facilitates the extraction of data from source databases, transformation of data into the desired format, and loading it into target systems, thus streamlining data warehousing efforts.

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phData

SEPTEMBER 25, 2024

While numerous ETL tools are available on the market, selecting the right one can be challenging. There are a few Key factors to consider when choosing an ETL tool, which includes: Business Requirement: What type or amount of data do you need to handle? It can onboard chunks of data from different systems into one.

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