use of data, information technology, statistical analysis, quantitative methods, and mathematical or computer-based models to help managers gain improved insight about their business operations and make better, fact-based decisions

a process of transforming data into actions through analysis and insights in the context of organizational decision making and problem solving.

supported by various tools such as Microsoft Excel and various Excel add-ins, commercial statistical software packages such as SAS or Minitab, and more complex business intelligence suites that integrate data with analytical software

__________use analytics to predict and prevent credit fraud.

use analytics for production planning, purchasing, and inventory management.

use analytics to recommend products to customers and optimize marketing promotions.

use it to get life-saving drugs to market more quickly.

use analytics to analyze historical sales data, understand customer behavior, improve Web site design, and optimize schedules and bookings.

use analytics to dynamically set prices over time to maximize revenue

are using business analytics to determine both game strategy and optimal ticket prices

ENUMERATION: small letters only give me 4 - p,m,c,l - ganyan layout hehe What are the common types of decisions that can be enhanced by using analytics?

TRUE OR FALSE the modern evolution of analytics began with the introduction of computers in the late 1940s and their development through the 1960s and beyond.

Modern computers provided the ability to store and analyze data in ways that were either very difficult or impossible to do so manually.

This facilitated the collection, management, analysis, and reporting of data,

The term business analytics coned by _____ in 1958 an IBM researcher

Select the 3 basic questions in business intelligence

What is the evolution of the modern discipline of BUSINESS INTELLIGENCE?

it been recognized as an important element of business, driven to a large extent by the massive growth of data in today’s world.

the basic tools of description, exploration, estimation, and inference, as well as more advanced techniques like regression, forecasting, and data mining.

was born from efforts to improve military operations prior to and during World War II.

is the leading professional society devoted to OR/MS and analytics, and publishes a bimonthly magazine called Analytics

What is the meaning of INFORMS?

began to evolve in the 1960s by combining business intelligence concepts with OR/MS models to create analytical-based computer systems to support decision making.

What are the tree components of decision support systems?

It's used for storing data and allows the user to input, retrieve, update, and manipulate data.

consists of various statistical tools and management science models and allows the user to easily build, manipulate, analyze, and solve models.

provides the interface necessary for the user to interact with the data and model management components

summarizes data into meaningful charts and reports, for example, about budgets, sales, revenues, or cost.

It's typically answers, “How much did we sell in this region”, “What was our revenue and profit last quarter.”

seeks to predict the future by examining historical data, detecting patterns or relationships in these data, and then extrapolating these relationships forward in time.

helps to answer questions such as “What will happen if demand falls by 10% or if supplier prices go up 5%?” “What do we expect to pay for fuel over the next several months?” “What is the risk of losing money in a new business venture?”

Select the 5 variety of tools used to support business analytics

addresses questions such as “How much should we produce to maximize profit?” “What is the best way of shipping goods from our factories to minimize costs?” “Should we change our plans if a natural disaster closes a supplier’s factory: if so, by how much?”

What are the 3 example of DECISION SUPPORT SYSTEMS (DSS)

WHAT KIND OF ANALYTICS for example, review business performance to find problems or areas of opportunity, and identify patterns and trends in data

For example, a marketer might wish to predict the response of different customer segments to an advertising campaign, a commodities trader might wish to predict short-term movements in commodities prices, or a skiwear manufacturer might want to predict next season’s demand for skiwear of a specific color and size.

For example, we may determine the best pricing and advertising strategy to maximize revenue, the optimal amount of cash to store in ATMs, or the best mix of investments in a retirement portfolio to manage risk.