Data Lake Data mining Data Quality 
DataKitchen
OCTOBER 11, 2021
Figure 2: Example data pipeline with DataOps automation. In this project, I automated data extraction from SFTP, the public websites, and the email attachments. The automated orchestration published the data to an AWS S3 Data Lake. All the code, Talend job, and the BI report are version controlled using Git.
CIO Business Intelligence
NOVEMBER 28, 2023
With each game release and update, the amount of unstructured data being processed grows exponentially, Konoval says. This volume of data poses serious challenges in terms of storage and efficient processing,” he says. To address this problem RetroStyle Games invested in data lakes. Quality is job one.
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AWS Big Data
AUGUST 1, 2024
Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI). This exercise is mostly undertaken by QA teams.
Jedox
OCTOBER 22, 2020
In addition to using data to inform your future decisions, you can also use current data to make immediate decisions. Some of the technologies that make modern data analytics so much more powerful than they used t be include data management, data mining, predictive analytics, machine learning and artificial intelligence.
BizAcuity
APRIL 1, 2023
Several large organizations have faltered on different stages of BI implementation, from poor data quality to the inability to scale due to larger volumes of data and extremely complex BI architecture. Without a strong BI infrastructure, it can be difficult to effectively collect, store, and analyze data.
BizAcuity
JANUARY 31, 2023
Several large organizations have faltered on different stages of BI implementation, from poor data quality to the inability to scale due to larger volumes of data and extremely complex BI architecture. Without a strong BI infrastructure, it can be difficult to effectively collect, store, and analyze data.
IBM Big Data Hub
MARCH 14, 2024
Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.
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