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PowerCurve for Beginners: A Comprehensive Guide

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PowerCurve is a complete suite of decision-making solutions that help businesses make efficient, data-driven decisions. Whether you're new to PowerCurve or want to understand its core concepts, this guide will introduce you to chief features, applications, and benefits. What is PowerCurve? PowerCurve is a decision management software developed by Experian that allows organizations to automate and optimize decision-making processes. It leverages data analytics, machine learning, and business rules to provide actionable insights for risk assessment, customer management, fraud detection, and more. Key Features of PowerCurve Data Integration – PowerCurve integrates with multiple data sources, including internal databases, third-party data providers, and cloud-based platforms. Automated Decisioning – The platform automates decision-making processes based on predefined rules and predictive models. Machine Learning & AI – PowerCurve utilizes advanced analytics and AI-driven models ...
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Big Data:Top Hadoop Interview Questions (2 of 5)

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Frequently asked Hadoop interview questions.


1. What is Hadoop?Hadoop is a framework that allows users the power of distributed computing.

2.What is the difference between SQL and Hadoop?

SQL is allowed to work with structured data. But SQL is most suitable for legacy technologies. Hadoop is suitable for unstructured data. And, it is well suited for modern technologis.
Hadoop

3. What is Hadoop framework?

It is distributed network of commodity servers(A server can contain multiple clusters, and a cluster can have multiple nodes)

4. What are 4 properties of Hadoop?

Accessible-Hadoop runs on large clusters of commodity machinesRobust-An assumption that low commodity machines cause many machine failures. But it handles these tactfully. Scalable-Hadoop scales linearly to handle larger data by adding more nodes to the cluster. Simple-Hadoop allows users to quickly write efficient parallel code

5. What kind of data Hadoop needs?

Traditional RDBMS having relational structure with data resides in tables. In Hadoop. data should be in Key,Value pair.

6. Is Hadoop suitable for on the fly processing?

Hadoop is not suitable. It is suitable only for off-line processing. That means, we can not use Hadoop on active web logs. We can use it on web logs data,which already generated. So, in this property Hadoop is matching to traditional data warehouses.

7. What is Map reduce?

Map reduce is a data processing model, which contain mappers, and reducers. It takes unstructred data as input, and create as Key,Value pairs for processing on Hadoop.

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