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The power of remote engine execution for ETL/ELT data pipelines

IBM Journey to AI blog

Unified, governed data can also be put to use for various analytical, operational and decision-making purposes. This process is known as data integration, one of the key components to a strong data fabric. The remote execution engine is a fantastic technical development which takes data integration to the next level.

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What is Data Integration in Data Mining with Example?

Pickl AI

Here comes the role of Data Mining. Read this blog to know more about Data Integration in Data Mining, The process encompasses various techniques that help filter useful data from the resource. Moreover, data integration plays a crucial role in data mining.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

However, efficient use of ETL pipelines in ML can help make their life much easier. This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines.

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What exactly is Data Profiling: It’s Examples & Types

Pickl AI

Accordingly, the need for Data Profiling in ETL becomes important for ensuring higher data quality as per business requirements. The following blog will provide you with complete information and in-depth understanding on what is data profiling and its benefits and the various tools used in the method.

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What is Integrated Business Planning (IBP)?

IBM Journey to AI blog

By having real-time data at their fingertips, decision-makers can adjust their strategies, allocate resources accordingly, and capitalize on the unexpected spike in demand, ensuring customer satisfaction while maximizing revenue. Data integration and analytics IBP relies on the integration of data from different sources and systems.

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Harmonize data using AWS Glue and AWS Lake Formation FindMatches ML to build a customer 360 view

Flipboard

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.

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Data architecture strategy for data quality

IBM Journey to AI blog

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Learn more about the benefits of data fabric and IBM Cloud Pak for Data.