Data Integration Data Transformation Finance 
CIO Business Intelligence
AUGUST 9, 2024
As part of its plan, the IT team conducted a wide-ranging data assessment to determine who has access to what data, and each data source’s encryption needs. As part of its plan, the IT team conducted a wide-ranging data assessment to determine who has access to what data, and each data source’s encryption needs.
Wayne Yaddow
FEBRUARY 6, 2025
Common challenges and practical mitigation strategies for reliable data transformations. Photo by Mika Baumeister on Unsplash Introduction Data transformations are important processes in data engineering, enabling organizations to structure, enrich, and integrate data for analytics , reporting, and operational decision-making.
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CIO Business Intelligence
FEBRUARY 16, 2023
But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. Digitizing was our first stake at the table in our data journey,” he says.
Cloudera
JUNE 1, 2021
These acquisitions usher in a new era of “ self-service ” by automating complex operations so customers can focus on building great data-driven apps instead of managing infrastructure. Datacoral powers fast and easy data transformations for any type of data via a robust multi-tenant SaaS architecture that runs in AWS.
Ontotext
MARCH 20, 2024
In today’s data-driven world, businesses are drowning in a sea of information. Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Zenia Graph’s Salesforce Accelerator makes this a reality.
AWS Big Data
SEPTEMBER 13, 2024
CFM takes a scientific approach to finance, using quantitative and systematic techniques to develop the best investment strategies. To share data to our internal consumers, we use AWS Lake Formation with LF-Tags to streamline the process of managing access rights across the organization.
Alation
OCTOBER 28, 2021
Too much access increases the risk that data can be changed or stolen. Remove Low Quality, Unused, or “Stale” Data. In healthcare especially, data integrity is incredibly important. Low quality, unused, or “stale” data can negatively impact research by skewing findings. Accountability is important.
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