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8 data strategy mistakes to avoid

CIO Business Intelligence

At Vanguard, “data and analytics enable us to fulfill on our mission to provide investors with the best chance for investment success by enabling us to glean actionable insights to drive personalized client experiences, scale advice, optimize investment and business operations, and reduce risk,” Swann says.

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What is a data engineer? An analytics role in high demand

CIO Business Intelligence

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer vs. data architect.

Analytics 126
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The 10 most in-demand IT jobs in finance

CIO Business Intelligence

The average salary for a full stack software engineer is $115,818 per year, with a reported salary range of $85,000 to $171,000 per year, according to data from Glassdoor. The average salary for a data engineer is $118,915 per year, with a reported salary range of $87,000 to $177,000 per year, according to data from Glassdoor.

Finance 98
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The 10 most in-demand IT jobs in finance

CIO Business Intelligence

The average salary for a full stack software engineer is $115,818 per year, with a reported salary range of $85,000 to $171,000 per year, according to data from Glassdoor. The average salary for a data engineer is $118,915 per year, with a reported salary range of $87,000 to $177,000 per year, according to data from Glassdoor.

Finance 98
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What is a Data Pipeline?

Jet Global

ETL pipelines are commonly used in data warehousing and business intelligence environments, where data from multiple sources needs to be integrated, transformed, and stored for analysis and reporting. Technologies used for data ingestion include data connectors, ingestion frameworks, or data collection agents.

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Top 10 Analytics Trends for 2019

Timo Elliott

Compliance drives true data platform adoption, supported by more flexible data management. As it has been for the last forty years, data collection, preparation, and standardization remain the most challenging aspects of analytics. Comprehensive governance and data transparency policies are essential.

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Data democratization: How data architecture can drive business decisions and AI initiatives

IBM Big Data Hub

Data within a data fabric is defined using metadata and may be stored in a data lake, a low-cost storage environment that houses large stores of structured, semi-structured and unstructured data for business analytics, machine learning and other broad applications.