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Enterprise Data Warehouse Modernization Workshop

Leverage The Advanced Analytical Features Of Google Cloud’s BigQuery To Deliver Business Value

On-demand Workshop | in-person and Online
Date & Time : Flexible
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About Niveus

At Niveus, we are dedicated to maximizing business outcomes through data modernization. With our industry expertise in BFSI, healthcare, automotive, media & entertainment, and digital, we have helped numerous businesses achieve their goals through the power of data. Our team of 70+ cloud engineers are equipped with the skills and knowledge necessary to take on any data-related challenge. Whether it’s data engineering, data modeling, reporting, or AI/ML, we have the expertise to handle it all.

Agenda

  • Analyze Highly Complex Data With Flexible Scalability for Spikes
  • Join Data Of Multiple Types from Internal & External Sources
  • Safely Secure & Share Data Across Business Units
  • Easily Run Real-Time Analytics & Reduce Time to Actionable Insights
  • Build & Operationalize Ml Solutions Directly in BigQuery

Takeaways for attendees

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Gain understanding of BigQuery functionalities

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Reference architecture for Data Warehouse Modernization

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Hands on experience with advanced analytical features on BigQuery

BUSINESS USE CASE

The tutorial aims to create clusters of data for descriptive analytics of London’s Santander Cycle Hire Scheme, leveraging geospatial analytics functions, & using K-Means algorithm in BigQueryML.

DAY

01

  • Smart Analytics Overview Slides
  • Workshop Setup
  • Serverless Scaling with BigQuery Lab
  • In-Memory Analytics with BI engine lab
  • Google BigQuery Administration & Security Lab
  • Data Migration Services Lab

DAY

02

  • Create a dataset to store your model
  • EDA for the use case dataset
  • Data visualization with Looker Studio Lab
  • Looker Overview :
  • ML model building using BigQuery
  • Model deployment & online prediction
  • Use the model to make data-driven decisions
  • Sharing data with relevant teams using analytics hub data exchange
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No Prerequisites

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Does Not Require Access To Any Data

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Only Uses Publicly Available Datasets

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Full hands-on lab exercises created by our experts

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Tools Used:
BigQuery, BigQueryML, Public Dataset

 

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