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5 Hardware Accelerators Every Data Scientist Should Leverage

Smart Data Collective

It helps developers create and maintain highly effective machine learning applications that operate in the cloud. Among other benefits, this helps make sure global computing resources are used as efficiently as possible and allows data science companies to take advantage of these resources at a reduced cost. IBM Watson Studio.

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How to Run Successful Predictive Analytics Project for your Business

Marutitech

While working on a predictive analytics project, the primary concern of any data scientist is to get reliable and unbiased results from the predictive analytics models. And that is only possible when common mistakes while implementing predictive analytics are avoided. Consider statistical implementation.

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How to Optimize Your Data Warehouse Investments

Domo

With Domo’s federated data model , you can query data from your existing data lakes and warehouses without moving or duplicating the data in Domo. The benefits of data federation. This allows you to optimize your data warehouse investments without having to recreate anything from scratch.

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Data Modelling for Analytics

The BAWorld

And therefore, to figure all this out, data analysts typically use a process known as data modeling. It forms the crucial foundation for turning raw data into actionable insights. Data modeling designs optimal data structures and relationships for storage, access, integrity, and analytics.

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150+ Top Global Cloud Thought Leaders and Next Generation Leaders of 2021

Whizlabs

He guest blogs at Oracle, IBM, HP, SAP, SAGE, Huawei, Commvault, Equinix, Cloudtech. The engineering team he leads is responsible for building and maintaining Microsoft Azure, Dynamics 365, Windows/Windows Server, HoloLens, Visual Studio/Visual Studio Code, GitHub, SQL Server, and Power BI. . Maximiser, Miller Heiman and more.

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Top Legacy Modernization Tools for 2024

Astera

Example: An online retailer moves its e-commerce application from an on-premises IBM WebSphere server using Java EE to AWS for better scalability and performance. The replatforming involves rehosting the application on AWS Elastic Beanstalk migrating the database from IBM DB2 to Amazon RDS for PostgreSQL.

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Build Data Warehouse with Concentrated Teams

Astera

Data Architects : Define a data architecture framework, including metadata, reference data, and master data. . DW Analysts : Identify data requirements and help design databases for storing information from disparate sources. . Use flexible data schemas . Data Warehouse Automation. .