Data Processing Data Science Unstructured Data 
Analytics Vidhya
OCTOBER 9, 2022
This article was published as a part of the Data Science Blogathon. Introduction Textual data from social media posts, customer feedback, and reviews are valuable resources for any business. There is a host of useful information in such unstructured data that we can discover.
DataKitchen
APRIL 13, 2021
Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix.
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CIO Business Intelligence
OCTOBER 2, 2024
As the world moves toward a cashless economy that includes electronic payments for most products and services, financial institutions must also deal with new risk exposures presented by mobile wallets, person-to-person (P2P) payment services, and a host of emerging digital payment systems.
IBM Big Data Hub
JULY 6, 2023
While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.
Domino Data Lab
JULY 2, 2019
In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. The approach they’ve used applies to other popular data science APIs such as NumPy , Tensorflow , and so on.
CIO Business Intelligence
JUNE 14, 2023
How is it possible to manage the data lifecycle, especially for extremely large volumes of unstructured data? Unlike structured data, which is organized into predefined fields and tables, unstructured data does not have a well-defined schema or structure.
Cloudera
AUGUST 31, 2020
As SMG continued to innovate, the scale, variety and velocity of data made its legacy warehouse environment show its limits. LLAP operates on open columnar data formats like ORC which are often used by Data Science tools like Spark, seamlessly enabling AI and Data Science on the same datasets. .
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