BOOKS - OS AND DB - Data Mining and Data Warehousing Principles and Practical Techniq...
Data Mining and Data Warehousing Principles and Practical Techniques - Parteek Bhatia 2019 PDF Cambridge University Press BOOKS OS AND DB
ECO~19 kg CO²

2 TON

Views
11034

Telegram
 
Data Mining and Data Warehousing Principles and Practical Techniques
Author: Parteek Bhatia
Year: 2019
Pages: 513
Format: PDF
File size: 39.2 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Data Smart Using Data Science to Transform Information into Insight, 2nd Edition
Unifying Business, Data, and Code Designing Data Products With JSON Schema
Real-Time Data Analytics for Large Scale Sensor Data Volume Six
Data Is Everybody|s Business: The Fundamentals of Data Monetization (Management on the Cutting Edge)
Data Smart Using Data Science to Transform Information into Insight, 2nd Edition
Power BI Give Life to Your Data With the Complete and Fastest Crash Course on Data Visualization
Azure Data Factory by Example Practical Implementation for Data Engineers, 2nd Edition
IBM Cloud Pak for Data: An enterprise platform to operationalize data, analytics, and AI
Data Pipelines Pocket Reference Moving and Processing Data for Analytics (Final)
Analytics in a Big Data World The Essential Guide to Data Science and its Applications
Big Data in Astronomy Scientific Data Processing for Advanced Radio Telescopes
Data Quality Engineering in Financial Services Applying Manufacturing Techniques to Data
Fuzzy Data Matching with SQL Enhancing Data Quality and Query Performance
Data Visualisation A Handbook for Data Driven Design 2nd Edition
Data Analytics and Machine Learning Navigating the Big Data Landscape
Data Analytics and Machine Learning Navigating the Big Data Landscape
Network Security through Data Analysis From Data to Action, 2nd Edition
Data as a Service A Framework for Providing Reusable Enterprise Data Services
Foundations for Architecting Data Solutions Managing Successful Data Projects
Python Data Science Handbook: Essential Tools for Working with Data
Data and AI Driving Smart Cities (Studies in Big Data, 128)
Fundamentals of Data Engineering: Plan and Build Robust Data Systems
SQL for Data Analysis: Advanced Techniques for Transforming Data into Insights
Python Data Science Handbook Essential Tools for Working with Data
Data Wrangling on AWS: Clean and organize complex data for analysis
Agile Data Science Building Data Analytics Applications with Hadoop
I Heart Logs Event Data, Stream Processing, and Data Integration
Multi-dimensional Urban Sensing Using Crowdsensing Data (Data Analytics)
Introduction to Data Science Data Wrangling and Visualization with R, 2nd Edition
Data Mesh Delivering Data-Driven Value at Scale (Third Early Release)
Effective Data Science Infrastructure How to Make Data Scientists Productive
R for Data Science Import, Tidy, Transform, Visualize, and Model Data
The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R
The Visual Organization Data Visualization, Big Data, and the Quest for Better Decisions
The Self-Service Data Roadmap Democratize Data and Reduce Time to insight (Early Release)
Big Data and Analytics for Beginners: Navigating the World of Data-Driven Decision Making
Data Science Essentials with R Learn with focus on data manipulation, visualization, and machine learning
Humanities Data in R Exploring Networks, Geospatial Data, Images, and Text, 2nd Edition
Behavioral Data Analysis with R and Python Customer-Driven Data for Real Business Results
The Data Preparation Journey: Finding Your Way with R (Chapman and Hall CRC Data Science Series)