Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. At the heart of this process lie ETL Tools—Extract, Transform, Load—a trio that extracts data, tweaks it, and loads it into a destination. Choosing the right ETL tool is crucial for smooth data management. What is ETL?

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Pickl AI

JANUARY 28, 2025

documents and images). This involves several key processes: Extract, Transform, Load (ETL): The ETL process extracts data from different sources, transforms it into a suitable format by cleaning and enriching it, and then loads it into a data warehouse or data lake. Data can be structured (e.g., databases), semi-structured (e.g.,

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

DagsHub

OCTOBER 23, 2024

For instance, if the collected data was a text document in the form of a PDF, the data preprocessing—or preparation stage —can extract tables from this document. The pipeline in this stage can convert the document into CSV files, and you can then analyze it using a tool like Pandas. Unstructured.io

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Pickl AI

OCTOBER 10, 2024

It integrates well with cloud services, databases, and big data platforms like Hadoop, making it suitable for various data environments. Typical use cases include ETL (Extract, Transform, Load) tasks, data quality enhancement, and data governance across various industries. Auditing helps track changes and maintain data integrity.

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DagsHub

NOVEMBER 11, 2024

Textual Data Textual data is one of the most common forms of unstructured data and can be in the format of documents, social media posts, emails, web pages, customer reviews, or conversation logs. These capture the semantic relationships between words, facilitating tasks like classification and clustering within ETL pipelines.

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Mlearning.ai

JULY 10, 2023

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. The single most common way to create a view in a dataset is by CREATE VIEW DDL statement and you can refer to the official documentation to explore more options.

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The MLOps Blog

MAY 31, 2023

To store Image data, Cloud storage like Amazon S3 and GCP buckets, Azure Blob Storage are some of the best options, whereas one might want to utilize Hadoop + Hive or BigQuery to store clickstream and other forms of text and tabular data. One might want to utilize an off-the-shelf ML Ops Platform to maintain different versions of data.

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