Big Data Analytics: Disruptive Technologies for Changing the by Dr. Arvind Sathi

By Dr. Arvind Sathi

Bringing a practitioner’s view to special info analytics, this paintings examines the drivers in the back of tremendous information, postulates a collection of use instances, identifies units of answer parts, and recommends a variety of implementation methods. This paintings additionally addresses and carefully solutions key questions about this rising subject, together with What is gigantic facts and the way is it getting used? How can strategic plans for giant information analytics be generated? and How does mammoth info swap analytics architecture? the writer, who has greater than twenty years of expertise in info administration structure and supply, has drawn the cloth from a wide breadth of workshops and interviews with company and data expertise leaders, supplying readers with the most recent in evolutionary, innovative, and hybrid methodologies of relocating ahead to the courageous new international of massive info.

Show description

Read or Download Big Data Analytics: Disruptive Technologies for Changing the Game PDF

Best management information systems books

Integrated Information Management: Applying Successful Industrial Concepts in IT (Business Engineering)

This booklet addresses the demanding situations dealing with details administration (IM) and offers useful resolution propositions. the 1st part describes six present traits and demanding situations to IM. the second one part introduces a accomplished version of built-in details administration (IIM). The 3rd part, utilizing six functional examples, describes how chosen options of IIM should be carried out.

Homeland Security Preparedness and Information Systems: Strategies for Managing Public Policy

Native land defense details platforms are an immense region of inquiry a result of large effect details structures play at the practise and reaction of presidency to a terrorist assault or ordinary catastrophe. place of birth safeguard Preparedness and knowledge platforms: innovations for dealing with Public coverage delves into the problems and demanding situations that public managers face within the adoption and implementation of data platforms for place of origin safeguard.

Active Knowledge Modeling of Enterprises

Firm Modeling has been outlined because the paintings of externalizing company wisdom, i. e. , representing the center wisdom of the company. even though necessary in product layout and structures improvement, for modeling and model-based techniques to have a extra profound impact, a shift in modeling ways and methodologies is important.

Additional resources for Big Data Analytics: Disruptive Technologies for Changing the Game

Sample text

For a 100-million-subscriber CSP, the CDRs could easily exceed 5 billion records a day. 2 Velocity There are two aspects to velocity, one representing the throughput of data and the other representing latency. Let us start with throughput, which represents the data moving in the pipes. 8 exabytes per month in 20164 as consumers share more pictures and videos. To analyze this data, the corporate analytics infrastructure is seeking bigger pipes and massively parallel processing. Latency is the other measure of velocity.

1 shows the monitoring station with the dashboard. Big Data Analytics can be used to monitor social media for feedback on product, price, and promotions as well as to automate the actions taken in response to the feedback. This may require communication with a number of internal organizations, tracking a product or service problem, and dialog with customers as the feedback results in product or service changes. When consumers provide feedback, the dialog can only be created if the responses are provided in low latency.

How many users could use the product to perform basic functions offered by the product? What were the highest frequency functions? The next level of analysis is to understand component failures. How many times did the product fail to perform? Where were the failures most likely? What led to the failure? What did the user do after the failure? Can we isolate the component, replace it, and repair the product online? These analysis capabilities can now be combined with product changes to create a sophisticated test-marketing framework.

Download PDF sample

Rated 4.34 of 5 – based on 13 votes