Data Architecture: A Primer for the Data Scientist: Big Data, Data Warehouse and Data Vault
Price Rs.35,130.00
Product Code:
012802044X
Weight:
1.78 Pounds
Availability: Instock in US ✔
Import from USA in Pakistan
Important: Delivery of this product will take 3 to 4 weeks.
- Before ordering any product, please make sure the product technically fulfills your need and contains no illegal ingredients (e.g., wine, alcohol, pig, pork, animal-based gelatin, etc.) or contents.
- For technical support or manufacturer's warranty of the products found on shoppingbag.pk, you can contact directly with the original manufacturer or visit their website.
- We are your importer of goods from the USA, UK, China, Russia, etc., and will not provide any technical support, product warranty, or quality check.
- Our enlarged and enhanced product pictures may differ slightly from the original products. Also, read product reviews and ratings before buying.
- Since dollar rate keeps fluctuating, prices are not confirmed on our website.
- We take 30% advance of the total value and the remaining payment is done at the time of delivery.
- We are assuming you have read our terms and conditions and agreed with them.
Product Detail
Today, the world is trying to create and educate data scientists because of the phenomenon of Big Data. And everyone is looking deeply into this technology. But no one is looking at the larger architectural picture of how Big Data needs to fit within the existing systems (data warehousing systems). Taking a look at the larger picture into which Big Data fits gives the data scientist the necessary context for how pieces of the puzzle should fit together. Most references on Big Data look at only one tiny part of a much larger whole. Until data gathered can be put into an existing framework or architecture it can’t be used to its full potential. Data Architecture a Primer for the Data Scientist addresses the larger architectural picture of how Big Data fits with the existing information infrastructure, an essential topic for the data scientist.
Drawing upon years of practical experience and using numerous examples and an easy to understand framework. W.H. Inmon, and Daniel Linstedt define the importance of data architecture and how it can be used effectively to harness big data within existing systems. You’ll be able to:
- Turn textual information into a form that can be analyzed by standard tools.
- Make the connection between analytics and Big Data
- Understand how Big Data fits within an existing systems environment
- Conduct analytics on repetitive and non-repetitive data
- Discusses the value in Big Data that is often overlooked, non-repetitive data, and why there is significant business value in using it
- Shows how to turn textual information into a form that can be analyzed by standard tools.
- Explains how Big Data fits within an existing systems environment
- Presents new opportunities that are afforded by the advent of Big Data
- Demystifies the murky waters of repetitive and non-repetitive data in Big Data
