BUS 340 Test 1

components of information system

computer hardware software data procedures people

Information/Function Silo

condition that exists when data are isolated in separate information systems; come into existence as entities at one organizational level creating information systems that meet only their particular needs

inherent processes best practices

save money & time in business process reengineering eliminate costs of developing complex applications in house

business analytics

scientific process of transforming data into insight for making better decisions; used for data driven or fact based decision making

in database analytics

speeds time to insights & enables better data governance by performing data integration & analytic functions inside the database so you don't have to move or convert data repeatedly

BI

Business Intelligence - combines architectures, tools, databases, analytical tools, applications, and methodologies; major objective to enable interactive access to data, enable manipulation of data, and give business managers and analysts the ability to conduct appropriate analysis

CRM

Customer Relationship Management - suite of applications, a database, and a set of inherent processes; 4 phases - marketing, customer acquisition, relationship management, loss/church; intended to support customer centric organizations

DSS

Decision Support Systems - interactive computer based systems, which help decision makers utilize data and models to solve unstructured problems

enterprise systems

ERP - SAP CRM - salesforce.com

ERP

Enterprise Resource Planning - suite of applications, a database, and a set of inherent business processes for consolidating business operations into a single consistent computing platform; purpose is integration of purchasing, human resources, production, sales, and accounting data into a single system

IS

Information System - assembly of hardware, software, data, procedures, and people that produces information

IT

Information Technology - refers to the products, methods, inventions, and standards that are used for the purpose of producing information

big data technologies

MapReduce Hadoop

MIS

Management Information Systems - management and use of information systems that help businesses achieve their strategies

predictive analytics

aims to determine what's likely to happen in the future

reengineering business processes

altering & designing business processes to take advantage of new information systems

appliances

brings together hardware & software in physical unit that's fast and scalable

key big data vendors

cloudier mapR hortonworks

information silo problems

data duplication/ inconsistency disjointed processes limited info & lack in integrated info isolated decisions lead to organizational inefficiencies increased expenses

stream analytics

data in motion analytics/real time data analytical; used for the analytic process of extracting actionable information form continuously flowing/streaming data

challenges with installing enterprise systems

determine current & ERP models, remove inconsistencies, implement the ERP application

MapReduce

distributes processing of large multi-structured data files across large cluster of machines; achieves high performance with "simple" computers

Information System

group of components that interact to produce information

strong passwords

have 10 or more characters (preferably 12) doesn't contain username, real name, or company name doesn't contain a complete dictionary word in any language different from previous passwords contains upper & lower case letters, numbers, and special characters

big data infrastructure

in memory analytics in database analytics grid computing appliances

descriptive analytics

knowing what's happening in the organization and understanding underlying trends and causes of occurrences

big data

means different things to people w/ different backgrounds and interests; used to describe the massive volumes of data analyzed by huge organizations

supply chain & bullwhip effect

natural dynamic of multistage supply chain, variability in size & timing of orders increase at each stage up supply chain, unrelated to erratic customer demand, large demand fluctuations force distributors, manufactures, suppliers to carry larger inventories, reduces overall profitability of supply chain, eliminate by giving supply chain participants access to consumer demand info

data science

new term for data analytics

Moore's Law

number of transistors per square inch on an integrated chip doubles every 18 months

Big Data V's

volume variety velocity veracity variability value proposition value

Hadoop

open source framework for processing, storing, and analyzing massive amounts of distributed, unstructured data; multiple products, open source, ecosytem

how to succeed with big data

predict outcome & trends identify associations b/t events & outcomes assess & measure the sentiments profile/cluster groups w/ similar behavioral patterns

supply chain management system

procurement, sales order processing, inventory management, and related activities

grid computing

promotes efficiency, lower cost, and better performance by processing jobs in shared, centrally managed IT resources

how enterprise systems solve the problem of information silos

puts all the data into one system and eliminates the silos

prescriptive analytics

recognizing what's going on as well as forecast and make decisions to achieve best performance possible

how do information systems affect supply chain performance

reduce costs of buying and selling increase supply chain speed reduce size & costs of inventories improve delivery scheduling fix bullwhip effect don't optimize supply chain profitability

Connections between DSS and BI

similar architectures since BI evolved from DSS, but BI uses data warehouses & DSS may or may not DSS constructed to directly support specific decision making but BI indirectly supports DSS is oriented toward analysts but BI has executive and strategy orientation DSS constructed to create solutions for unstructured problems but BI constructed w/ tools fit to needs of organization DSS methods were created in academic world but BI developed by software companies many tools BI uses are also DSS tools

in memory analytics

solves complex problems in near real time w/ highly accuracy insights by allowing analytical computations & big data to be processed in memory & distributed across set of nodes

data warehousing

system used for reporting and data analysis; considered a core component of BI; integrating data that provides business value

data scientist

use a combination of business and technical skills to investigate big data to improve current business analytics practices and improve decisions; high salaries & expectations

data analyst

translates data into plain english; takes data and uses it to help companies make better decisions