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Data Lake Architectural Components

Modern data analytics is moving past the Data Warehouse to the Data Lake to utilize emerging technologies for predicting behaviour, not just reporting on what has passed. The organization today though aware of the capabilities of data lake, lack maturity

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calenderJuly 28, 2017

Tableau Performance Optimization

Tableau is a powerful collaboration platform. One can easily create, share and distribute the workbooks and dashboards set up in Tableau. Since people across the organization depend on Tableau, it’s essential to keep it performant and scalable. We need to understand

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Author Name Posted by Gaurav Mittal
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calenderJuly 18, 2017

Building Data Lake on AWS

Data Lake on Cloud vs. On-Premises The dynamics of working with data in a Data Lake often calls for rapid provisioning of computing & storage resources, scaling up or down in response to data flows, and processing needs. Until recently, Hadoop was

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Author Name Posted by Eshan Jain
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calenderJuly 17, 2017

Big Data on AWS an Introduction

Analyzing large data sets requires significant computing capacity that can vary in size based on the amount of input data and the type of analysis. This characteristic of big data workloads is ideally suited to the pay-as-you-go cloud computing model,

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Author Name Posted by Ankur Jain
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calenderJuly 11, 2017

Take a Leap from Big Data to Big Value with SAP HANA 2.0

SAP HANA is a game changer when it comes to data processing and analytics. Data Modeling is the core of HANA application development. Primarily , Data Modeling is a fusion of both ETL ( extract , transform, load )

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Author Name Posted by S.Suresh
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calenderJune 30, 2017

Data Lake – An Overview

The explosion of new types of data in recent years has put tremendous pressure on the datacentre, both technically and financially, and an architectural shift is underway where Enterprise Hadoop is playing a key role in the resulting modern data

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Author Name Posted by Anand Agrawal
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calenderJune 13, 2017
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