ISDS Ch 6

because data ________ has always been a challenging issue in IT, and it is getting even more puzzling with the advent of Big Data. More than 80 countries have data privacy laws. The European Union (EU) defines seven "safe harbor privacy principles" for the protection of their citizens' private data. In the US, Sarbanes-Oxley affects all publicly listed companies.

Govern

because blending data from disparate sources for your organization is an essential part of Big Data Analytics. Organizations that can blend different relational, semi-structured, and raw data sources in real time, without expensive up-front costs, will the ones that get the best value from Data.

Integrate

DOW Chemical Case Solution: "Thousands of DOW employees rely on...."

JMP Statistical Discovery Software to gain an competitive edge. JMPs used in many facets of DOW's operations

because it is hard to keep track of all of the new database vendors, open source projects, and Big Data service providers. It will be even more crowded and complicated in the years ahead.

Simplify

How to Succeed with Big Data: SECEVIG

Simplify Evangelize Coexist Empower Visualize Integrate Govern

Challenges of Big Data Analytics? pp. 286-287

Skill availability (data scientists are in short supply)

It is a well-known fact that if you don't have committed executive backing, it is difficult (if not impossible) to succeed. If the scope is a single or a few analytical applications, the support can be at the departmental level. However, if the target is enterprise-wide organizational transformation, which is often the case for Big Data initiatives, _____________________ needs to be at the highest levels and organization-wide. Which one best Critical Success Factor for Big Data Analytics best fills the blank in the previous sentence?

Strong, committed sponsorship (executive champion)

MapReduce

is a technique popularized by Google that distributes the processing of very large multi-structured data files across a large cluster of ordinary machines/computer processors.

What have Traditional data warehouses not been able to do?

keep up with the variety and complexity of data

critical event processing

method of capturing, tracking, and analyzing streams of data to detect events (out of normal happenings) of certain types that are worthy of the effort.

Stream Analytics Applications: Health Services

- biggest potential source of Big Data comes from PATIENT MONITORING

What are the Critical Success Factors for Big Data Analytics

-A clear business need (alignment with the vision and the strategy) -Strong, committed sponsorship (executive champion) -a fact-based DMing Culture

6 V's of Big Data For the test, given the definition in the question, answer which trait is being described

1. Volume 2. Variety 3. Velocity 4. Veracity 5. Variability 6. Value Proposition

Business investments ought to be made for the good of the business, not for the sake of mere technology advancements. Therefore the main driver for Big Data analytics should be an alignment with the vision and the strategy and at any level-strategic, tactical, and operations. Which of the critical success factors for Big Data analytics is being described?

A clear business need

NoSQL (Not Only SQL)

A new style of database to store and process large volumes of unstructured, semi-structured, and multi-structured data Can handle Big Data better than traditional relational database technology

Stream Analytics

Analytic process of extracting actionable information from continuously flowing/streaming data AKA Data-in-motion Analytics & Real-Time Data Analytics One of the Vs in Big Data = Velocity

What is the value formula as related to Big Data?

Big Data + Big Analytics = Value

Data Scientist equals what?

Big data guru - One with skills to INVESTIGATE Big Data

because using the strengths of each database platform and enabling them to ____ in your organization's data architecture are essential. There is ample literature that talks about the necessity of maintaining and nurturing synchronicity of traditional data warehouses with the capabilities of new platforms

Coexist

DOW Chemical Case Main Point

DOW enhances reliability with advanced analytics in JMP and is adding billion in value with Six Sigma

What is the sexiest job of the 21st century according to Davenport and Patil?

Data Scientist

because Big Data and self-service business intelligence go hand in hand. Organizations with Big Data are over 70 percent more likely than other organizations to have BI/BA projects that are driven primarily by the business community, not by the IT group. Across a range of uses - from tackling new business problems, developing entirely new products and services, finding actionable intelligence in less than an hour, and blending data from disparate sources - Big Data has fired the imagination of what is possible through the application of analytics.

Empower

because with the backing of one or more executive sponsors, future business graduates from LSU E.J. Ourso College of Business like yourself can get the ball rolling and instill a virtuous cycle: The more departments in your organization realize actionable benefits, the more pervasive analytics becomes across your organization. Fast, easy-to-use visual analytics is the key that opens the door to organization-wide analytics adoption and collaboration.

Evangelize

Where does Big Data come from?

Everywhere, most of it is generated by machines

DOW Chemical Case Results: "As Dow transitions from traditional manufacturer to solutions provider, ......"

JMP now an essential tool for analyzing & presenting data, sharing it in a collaborative process with colleagues and customers, and using it to project new initiatives.

Where do data scientist come from?

M.S./Ph.D. in MIS, CS, IE,... and/or Analytics - LSU ISDS Masters of Science in Analytics

What are the 3 most important Big Data Technologies

MapReduce Hadoop NoSQL

Big Data meets Big Science at CERN: Holds the largest what? Where is it located

Particle Physics Lab Geneva, Switzerland

Definition of Big Data

Using data to understand customers/clients and business operations to sustain growth and profitability is: a) an increasingly challenging task for today's enterprises. b) is not a new technological fad, rather, it's a business priority.

This characteristic of Big Data is its potential to contain more useful patterns and interesting anomalies than "small" data

Value proposition

Data flows can be highly inconsistent, with periodic peaks, making data loads hard to manage.

Variability

Data today comes in all types of formats-ranging from traditional databases to hierarchical data stores created by the end users and OLAP systems, to text documents, e-mail, XML, meter-collected, sensor-captured data, to video, audio, and stock ticker data. By some estimates, 80 to 85 percent of all organizations' data is in some sort of unstructured or semi-structured format.

Variety

refers to both how fast data is being produced and how fast the data must be processed (i.e., captured, stored, and analyzed) to meet the need or demand. RFID tags, automated sensors, GPS devices, and smart meters are driving an increasing need to deal with torrents of data in near—real time.

Velocity

refers to the conformity to facts: accuracy, quality, truthfulness, or trustworthiness of Big Data

Veracity

because according to leading analytics research companies like Forrester and Gartner, enterprises find advanced data _________ platforms to be essential tools that enable them to monitor business, find patterns, and take action to avoid threats and snatch opportunities.

Visulaize

the most common trait of Big Data. Many factors contributed to the exponential increase in data ________, such as transaction-based data stored through the years, text data constantly streaming in from social media, increasing amounts of sensor data being collected, automatically generated RFID and GPS data, and so forth.

Volume

In ____?______, the numbers rather than intuition, gut feeling, or supposition drive decision making. There is also a culture of experimentation to see what works and doesn't. To create ____?____, senior management needs to do the following: recognize that some people can't or won't adjust; be a vocal supporter; stress that outdated methods must be discontinued; ask to see what analytics went into decisions; link incentives and compensation to desired behaviors.

a fact-based decision-making culture

Hadoop? Who was it created by?

open source framework for storing and analyzing large amounts of distributed, unstructured data Doug Cutting at Yahoo!

Big Data by itself, regardless of the size, type, or speed, is worthless unless ....

business users do something with it that delivers value to the organization.

The traditional means for capturing, storing, and analyzing data are not capable of what?

dealing with Big Data effectively and efficiently and so a new breed of technologies are needed to take on the Big Data (developed or purchased or hired or outsourced).

DOW Chemical Case Challenge: "To turn data into knowledge that...." P,FI,ID

ensures reliability of products, fosters innovation, and informs decisions

Perpetual Analytics

evaluates every incoming observations against all prior observations when analyzing Big Data Recognizing how the new observation relates to all prior observations enables the discovery of real-time insights.

A use case in the energy industry for stream analytics is a classic _____ application for the electric power supply chain. p. 316

smart grid

Data Scientist Facts

use a combination of business, communication, and technical skills to investigate Big Data looking for ways to improve current analytics practices and hence improve decisions for new business opportunities. Data scientist positions are in high demand and offered with very high salaries and very high expectations.