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Data architecture strategy for data quality

IBM Journey to AI blog

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

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Drowning in Data? A Data Lake May Be Your Lifesaver

ODSC - Open Data Science

Arjuna Chala, associate vice president, HPCC Systems For those not familiar with the HPCC Systems data lake platform, can you describe your organization and the development history behind HPCC Systems? They were interested in creating a data platform capable of managing a sizable number of datasets.

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? A data warehouse is a centralised repository that consolidates data from various sources for reporting and analysis. It is essential to provide a unified data view and enable business intelligence and analytics.

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Twilio Segment: Transforming customer experiences with AI

AI News

AI and machine learning (ML) models are incredibly effective at doing this but are complex to build and require data science expertise. HT: When companies rely on managing data in a customer data platform (CDP) in tandem with AI, they can create strong, personalised campaigns that reach and inspire their customers.

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Top Predictive Analytics Tools/Platforms (2023)

Marktechpost

IBM merged the critical capabilities of the vendor into its more contemporary Watson Studio running on the IBM Cloud Pak for Data platform as it continues to innovate. The platform makes collaborative data science better for corporate users and simplifies predictive analytics for professional data scientists.

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Exploring the AI and data capabilities of watsonx

IBM Journey to AI blog

By supporting open-source frameworks and tools for code-based, automated and visual data science capabilities — all in a secure, trusted studio environment — we’re already seeing excitement from companies ready to use both foundation models and machine learning to accomplish key tasks.

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A brief history of Data Engineering: From IDS to Real-Time streaming

Artificial Corner

Cloud-based data storage solutions, such as Amazon S3 (Simple Storage Service) and Google Cloud Storage, provide highly durable and scalable repositories for storing large volumes of data. It provided a platform for big data processing and machine learning, simplifying the process of building and deploying data pipelines.