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AI and the future of unstructured data

IBM Journey to AI blog

Data engineering teams have grown up around the rise of data warehousing and business intelligence applications over the last decade and historically have operated in the world of SQL, structured databases and business analytics processes designed for data analysts and C-suite consumers.

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Data Intelligence empowers informed decisions

Pickl AI

Data governance and security Like a fortress protecting its treasures, data governance, and security form the stronghold of practical Data Intelligence. Think of data governance as the rules and regulations governing the kingdom of information. It ensures data quality , integrity, and compliance.

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Comparing Tools For Data Processing Pipelines

The MLOps Blog

Scalability : A data pipeline is designed to handle large volumes of data, making it possible to process and analyze data in real-time, even as the data grows. Data quality : A data pipeline can help improve the quality of data by automating the process of cleaning and transforming the data.

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

Describe a situation where you had to think creatively to solve a data-related challenge. I encountered a data quality issue where inconsistent data formats affected the analysis. Data Governance and Ethics Questions What is data governance, and why is it important? 10% group discount available.

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Find Your AI Solutions at the ODSC West AI Expo

ODSC - Open Data Science

You’ll use MLRun, Langchain, and Milvus for this exercise and cover topics like the integration of AI/ML applications, leveraging Python SDKs, as well as building, testing, and tuning your work. In this session, we’ll demonstrate how you can fine-tune a Gen AI model, build a Gen AI application, and deploy it in 20 minutes.

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What is Hadoop and How Does It Work?

Pickl AI

Job Submission and Cluster Management: To take advantage of Hadoop, you generally use the Hadoop API to generate code in Java, Python, or other compatible languages. Aside from cluster management, responsibilities like data integration and data quality control can be difficult for organisations that use Hadoop systems.

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Drowning in Data? A Data Lake May Be Your Lifesaver

ODSC - Open Data Science

A 2019 survey by McKinsey on global data transformation revealed that 30 percent of total time spent by enterprise IT teams was spent on non-value-added tasks related to poor data quality and availability. They were interested in creating a data platform capable of managing a sizable number of datasets.