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Data Science vs Artificial Intelligence [Top 10 Differences]

Knowledge Hut

The field of Artificial Intelligence has seen a massive increase in its applications over the past decade, bringing about a huge impact in many fields such as Pharmaceutical, Retail, Telecommunication, energy, etc.

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Hadoop Use Cases

ProjectPro

These days we notice that many banks compile separate data warehouses into a single repository backed by Hadoop for quick and easy analysis. Hadoop clusters are used by banks to create more accurate risk analysis models for the customers in its portfolio. Predicting market behaviour is another classic problem in the financial sector.

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5 reasons why Business Intelligence Professionals Should Learn Hadoop

ProjectPro

The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services. Big data, multi-structured data, and advanced analytics.

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20 Solved End-to-End Big Data Projects with Source Code

ProjectPro

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. How do you Create a Good Big Data Project?

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100+ Big Data Interview Questions and Answers 2023

ProjectPro

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. Works with only structured data. Hardware Hadoop uses commodity hardware.

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What is Data Enrichment? Best Practices and Use Cases

Precisely

Determine what data you’ll need Once you’ve determined the use case, brainstorm and dig deeper into what your end goals are and what you need to know to get there. For example, will you need structured data, unstructured, or a combination?

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Five Strategies to Accelerate Data Product Development

Cloudera

From my discussions with Cloudera clients, data product development has been on top of the growth agenda in many industries such as Financial Services, Healthcare and Telecommunications. 4- Compose Data Experiences Organized around Value Propositions, Not Intermediate Data Outputs.