Data Ingestion Data Platform ETL 
AWS Machine Learning Blog
JUNE 18, 2024
This manual synchronization process, hindered by disparate data formats, is resource-intensive, limiting the potential for widespread data orchestration. The platform, although functional, deals with CSV and JSON files containing hundreds of thousands of rows from various manufacturers, demanding substantial effort for data ingestion.
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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Pickl AI
DECEMBER 16, 2024
Whether you aim for comprehensive data integration or impactful visual insights, this comparison will clarify the best fit for your goals. Key Takeaways Microsoft Fabric is a full-scale data platform, while Power BI focuses on visualising insights. Fabric suits large enterprises; Power BI fits team-level reporting needs.
The MLOps Blog
MARCH 15, 2023
A typical data pipeline involves the following steps or processes through which the data passes before being consumed by a downstream process, such as an ML model training process. Data Ingestion : Involves raw data collection from origin and storage using architectures such as batch, streaming or event-driven.
Pickl AI
OCTOBER 10, 2024
Its drag-and-drop interface makes it user-friendly, allowing data engineers to build complex workflows without extensive coding knowledge. Nifi excels in data ingestion, routing, transformation, and system-to-system data flow management. AWS Glue AWS Glue is a fully managed ETL service provided by Amazon Web Services.
The MLOps Blog
JANUARY 26, 2024
Keeping track of how exactly the incoming data (the feature pipeline’s input) has to be transformed and ensuring that each model receives the features precisely how it saw them during training is one of the hardest parts of architecting ML systems. This is where feature stores come in. What is a feature store?
ODSC - Open Data Science
SEPTEMBER 29, 2023
Arjuna Chala, associate vice president, HPCC Systems For those not familiar with the HPCC Systems data lake platform, can you describe your organization and the development history behind HPCC Systems? They were interested in creating a data platform capable of managing a sizable number of datasets.
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