isds 3 test 2
Metadata -
"data about data" In DW, describes the structure and meaning of the data, contributing to their effective use.
Outcome KPIs
(lagging indicators e.g., revenues)
Driver KPIs
(leading indicators e.g., sales leads)
Metric Management Reports
Help manage business performance through metrics (SLAs (service-level agreements) for externals; KPIs (key performance indicators) for internals) Can be used as part of Six Sigma and/or TQM (total quality management)
Dashboard-Type Reports
Graphical presentation of several performance indicators in a single page using dials/gauges
Monitoring -
Graphical, abstracted data to monitor key performance metrics.
Dependent data mart
A subset that is created directly from a data warehouse
Performance measurement system
A system that assists managers in tracking the implementations of business strategy by comparing actual results against strategic goals and objectives
Enterprise application integration (EAI)
A technology that provides a vehicle for pushing data from source systems into a data warehouse
Strategize,Plan,Monitor/analyze, Act/adjust
Process Steps of a closed loop
A DM(data marts)
can be a replication of a subset of data in the data warehouse.
DM
can be independent of or dependent on a data warehouse.
nominal and ordinal
categorical data types
Data visualization
is the use of visual representations to explore, make sense of, and communicate data.
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Data visualization techniques and tools
make the users of business analytics and BI systems better information consumers.
Traditional reporting
may be flat, slow to develop, and difficult to apply to specific situations.
Good scalability
means that queries and other data-access functions will grow linearly with the size of the warehouse
Descriptive statistics
methods can be used to measure central tendency, dispersion, or the shape of a given data set.
clarity, brevity, completeness, and correctness.
The key to any successful business report is
information visualization + predictive analytics
Visual Analytics is the combination of
Dice -
a slice on more than two dimensions
Slice -
a subset of a multidimensional array
time series forecasting
the use of mathematical modeling to predict future values of the variable of interest base on previously observed values.
descriptive statistics
describing the data as it is
hosted data warehouses
Another alternative to data warehouse development
Independent data mart
A small data warehouse designed for a strategic business unit or a department
Bar charts
- useful in displaying nominal data or numerical data that splits nicely into different categories so you can quickly see comparative results and trends within your data
Michigan's EDW has almost 10,000 users in five major departments, 20 agencies, and more than 100 bureaus. Just in the Department of Human Services, the EDW contributes to nearly every function, including accurate delivery of and accounting for benefits to almost 2.5 million clients receiving public assistance. It is safe to say that the EDW was large and complex.
2. What are the size and complexity of EDW used by state agencies in Michigan?
The challenge is not directly stated, but students should be aware that state governments struggle to balance budgets and satisfy a wide variety of needs. They also should recognize that a state operates many kinds of departments, so it likely could benefit from a unified source of information. The proposed solution was an enterprise (statewide) electronic data warehouse linking employees across departments. The obtained results include financial benefits worth $1 million per business day. Savings come from operational efficiencies, avoidance of sanctions, improved client outcomes, integrity benefits awarded to well-performing programs, and recovery of inappropriate benefits payments. The data warehouse has yielded a 15:1 cost-effectiveness ratio and improvements in the accurate delivery and accounting of benefits.
3. What were the challenges, the proposed solution, and the obtained results of the EDW?
The DMAIC performance model
A closed-loop business improvement model that encompasses the steps of defining, measuring, analyzing, improving, and controlling a process
Regression
A part of inferential statistics
Six Sigma
A performance management methodology aimed at reducing the number of defects in a business process to as close to zero defects per million opportunities (DPMO) as possible
Balanced Scorecard (BSC)
A performance measurement and management methodology that helps translate an organization's financial, customer, internal process, and learning and growth objectives and targets into a set of actionable initiatives
Business Performance Management (BPM)
A real-time system that alerts managers to potential opportunities, impending problems, and threats, and then empowers them to react through models and collaboration
Dimensional Modeling
A retrieval-based system that supports high-volume query access
Enterprise information integration (EII)
An evolving tool space that promises real-time data integration from a variety of sources, such as relational or multidimensional databases, Web services, etc.
Oper marts
An operational data mart
data
Analytics starts with
structured or unstructured.
At the highest level of abstraction, data can be classified as
A set of integrated, closed-loop management and analytic processes, supported by technology. Tools for businesses to define strategic goals and then measure/manage performance against them Methods and tools for monitoring key performance indicators (KPIs), linked to organizational strategy
BPM encompasses three key components
line, bar, and pie chart
Basic chart types include
Requires minimal investment in infrastructure Frees up capacity on in-house systems Frees up cash flow Makes powerful solutions affordable Enables solutions that provide for growth Offers better quality equipment and software Provides faster connections
Benefits of Hosted Data Warehouses:
OLTP (Online Transaction Processing)
Capturing and storing data from ERP, CRM, POS Day-to-day business transactions The main focus is on efficiency of routine tasks
Infrastructure
Columnar Real-time DW Data warehouse appliances Data management practices/technologies In-database & In-memory processing New DBMS New DBMS & Advanced analytics
Conduct a current situation analysis Determine the planning horizon Conduct an environment scan Identify critical success factors Complete a gap analysis Create a strategic vision Develop a business strategy Identify strategic objectives and goals
Common tasks for the strategic planning process:
OLAP (Online Analytical Processing)
Converting data into information for decision support Data cubes, drill-down / rollup, slice & dice Requesting ad hoc reports Conducting statistical and other analyses Developing multimedia-based applications
have the knowledge of high-performance software, hardware, and networking technologies possess solid business knowledge and insight be familiar with the decision-making processes so as to suitably design/maintain the data warehouse structure possess excellent communications skills
DWA should be technical and ...
Reduce dimension, reduce volume, and balance data
Data Reduction reduces what?
analytics tasks.
Data in its original/raw form is not usually ready to be useful in
data access, data federation, and change capture.
Data integration comprises three major processes:
Kimball Model:
Data mart approach (bottom-up)
Information visualization
Descriptive, backward focused "what happened" "what is happening"
There were challenges with the implementation due to the variability in the data itself and the complexity of the task.
Did they face any implementation challenges?
Strategy, Targets, Ranges, Encoding, Time frames, Benchmarks
Distinguishing features of KPIs
Inferential statistics
Drawing inferences about the population based on sample data
Inmon Model:
EDW approach (top-down)
Extract Transform Load
ETL =
Highly targeted data analytics play an ever more critical role in helping carriers secure or improve their standing in an increasingly competitive marketplace.
How can data warehousing and data analytics help TELCOs in overcoming their challenges?
The company was concerned about the diversity and disparity of the information that it was using to make decisions. By centralizing information, it was possible for them to create "one version of the truth" and create dashboards and reports that showed reliable information that could be used for decision making.
How did Electrabel use information visualization for the single version of the truth?
Scorecards give Expedia much better insight into customer satisfaction by providing staff, managers, and executives instant visualization and reporting of patterns and trends. Through KPIs, the scorecard also allows for comparison of the customer patterns and trends to Expedia's corporate goals and objectives.
How did Expedia.com improve customer satisfaction with scorecards?
The solution was to implement a system based on WebFOCUS software from Information Builders. As a result, FEMA staff can now browse insurance data posted on NFIP's BureauNet intranet site, select just the information they want to see, and get an onscreen report or download the data as a spreadsheet. This also allows them to create custom reports without having to go through their IT provider, CSC. The first major test of this system was Tropical Storm Allison, and BureauNet worked very well. It also has been able to scale up to handle increased demand.
How did FEMA improve its inefficient reporting practices?
They incorporated Tableau and Teknion to assist with visualizing and understanding their merchandising activities, involving the complete supply chain from manufacture to end customer.
How did the Dallas Cowboys use information visualization for its business operations?
The researchers generated a very detailed model using a wide array of variables available to them. You may see the listing of the variables in Table 2.5 in the case itself, but this is optional. Researchers used data analysis techniques to identify the important variables and understand their weight.
How did the researchers formulate/design the prediction problem (i.e., what were the inputs and output, and what was the representation of a single sample—row of data)?
The company decided to bring all marketing work in-house. It was determined that it was important for them to clean the data and manage it in a central repository. To do this they partnered with Teradata.
How did they implement the proposed solutions?
Scatter plots (visualization—for simple regression) Ordinary least squares method (A line that minimizes squared of the errors.)
How do we develop linear regression models?
R2 (R-Square) p Values Error measures (for prediction problems)
How do we know if the model is good enough?
Time series models are focused on extrapolating on their time-varying behavior to estimate the future values.
How is time series forecasting differ from simple linear regression?
A number of potential models were created, but the most accurate model indicates an accuracy of 86.48%. It is possible that accuracy could be improved in the future with the addition of new data points, both in the form of variables and completed games.
How successful were the prediction results? What else can they do to improve the accuracy?
analytics study.
Identifying, accessing, obtaining and processing of relevant data are the most essential tasks in any
They primarily provide services in automobiles.
In what type of market does SiriusXM conduct its business?
Balanced Scorecard-Type Reports
Include financial indicators and non-financial indicators (customer, business process, and learning & growth)
exponential growth in highly efficient visualization systems investment.
Increasing demand for visual analytics coupled with fast-growing data volumes led to
Data transformation tools are expensive Data transformation tools may have a long learning curve
Issues affecting the purchase of an ETL tool
The largest data-related challenge is the high volume of data available. This data is normally from multiple sources, and used primarily for multiple, different purposes. It is important to be able to aggregate all data, but at the same time identify data that truly affects student retention.
List and discuss the data-related challenges within context of this case study. about attrition
Customer performance Service performance Sales operations Sales plan/forecast
Operational areas covered by driver KPIs
Tactic-centric (operationally focused) Budget-centric plan (financially focused)
Operational planning can be
Predictive analytics
Predictive, future focused "what will happen" "why will it happen"
tedious, time-demanding, yet crucial task
Readying the data for analytics is
data visualizations
Related to information graphics, scientific visualization, and statistical graphics
Safeguarding the most valuable assets Government regulations (HIPAA, etc.) Must be explicitly planned and executed
Security and privacy is a pressing issue in DW
Data-Driven Marketing
Sirius XM Attracts and Engages a New Generation of Radio Consumers with
descriptive or inferential.
Statistical methods can be classified as either
BI and business analytics.
Statistics in general, and descriptive statistics in particular, is a critical part of
Analysis -
Summarized dimensional data to analyze the root cause of problems.
security and privacy
The ____ and _____ of data and information are critical issues for a data warehouse professional.
"last mile"
The ______ is the most challenging stage of the reporting process in which consolidated figures are cited, formatted, and described to form the final text of the report.
Multidimensional
The ability to organize, present, and analyze data by several dimensions, such as sales by region, by product, by salesperson, and by time (four dimensions)
Dashboard design
The fundamental challenge of dashboard design is to display all the required information on a single screen, clearly and without distraction, in a manner that can be assimilated quickly.
Star schema
The most commonly used and the simplest style of dimensional modeling Contain a fact table surrounded by and connected to several dimension tables
regression
The most widely known and used analytics technique in statistics
monitoring, analysis, management
Three layers of information of a dashboard.
Data acquisition software (back-end) The data warehouse that contains the data & software Client (front-end) software that allows users to access and analyze data from the warehouse
Three-tier architecture
corporations
Traditional reporting is still used in
First two tiers in three-tier architecture are combined into one
Two-tier architecture
data lakes
Unstructured data storage technology for Big Data
regression
Used to characterize relationship between explanatory (input) and response (output) variable
Sourcing
Web, social media, and Big Data Open source software SaaS (software as a service) Cloud computing Data lakes
While a large amount of data exists that can be used to possibly help predict the outcome of sporting events, understanding how all of that information works together and how important individual factors will be is quite challenging. Additionally there are individual actions that can occur on the day that may affect the outcome as well.
What are the foreseeable challenges in predicting sporting event outcomes (e.g., college bowl games)?
To stay competitive, TELCOs must continuously refine everything from customer service to plan pricing and use the power of highly targeted data analytics in helping the company secure or improve their standing in the highly competitive marketplace.
What are the main challenges for TELCOs (telecommunications companies)?
When a disaster occurs, FEMA is inundated with a huge amount of paperwork to sift through in order to administer the National Flood Insurance Program (NFIP). Sifting through this paperwork is very cumbersome and labor-intensive. Two floods occur at once: flood over the land and a flood of paperwork.
What are the main challenges that FEMA faces?
SiriusXM is a provider of satellite radio.
What does SiriusXM do?
Compromises the validity of the model. What do we do then? Identify the violations of the assumptions and use techniques to mitigate them.
What happens if the assumptions do NOT hold?
BIGS is the Business Intelligence and Global Standards program, a strategic initiative for management information and business intelligence. Its purpose is to deliver globally consistent and transparent management information across functions.
What is BIGS?
The Federal Emergency Management Agency (FEMA) is a U.S. federal agency that coordinates disaster response when the President declares a national disaster. This case illustrates the power and the utility of automated report generation for a large (and, at the time of natural disaster, somewhat chaotic) organization such as FEMA.
What is FEMA and what does it do?
Student attrition represents students who drop out or fail to complete a course of study. This is very important in higher education as it is a leading metric of the success of individual institutions.
What is student attrition, and why is it an important problem in higher education?
Applications are being developed relating to voter fraud, medical use, and other tax issues.
What other problems and challenges do you think federal and state governments are having that can benefit from BI and data warehousing?
Critical success factors Strategic goals and targets
What to monitor?
Management opted for a solution that included the move to a single data warehouse appliance. The team selected the IBM Netezza data appliance warehouse because of its flexibility in data modeling. Additionally, the group adopted a Scrum development model that allowed for rapid development.
What was the approach for a potential solution to AARP?
Result: Now, for the first time, the Dallas Cowboys are able to monitor their complete merchandising activities from manufacture to end customer and see not only what is happening across the life cycle, but drill down even further into why it is happening.
What was the obtained results from Dallas Cowboys?
Solution: Tableau and Teknion together provided real-time reporting and dashboard capabilities that provided the necessary visualization functionality to meet and exceed the Cowboys' requirements.
What was the proposed solution from Dallas Cowboys? and the obtained results?
The town installed 60,000 wireless meters in customers' homes and monitored the data through an online portal. A SAS solution was used to manage and analyze the data. The Town of Cary uses SAS analytics to analyze data from wireless water meters, assess demand, detect problems, and engage customers.
What was the proposed solution on the town of cary?
The solution uses a variety of data and controls for important variables to create a system to predict freshman attrition. As a result, the system used was able to predict that attrition with good accuracy, approximately 80%.
What was the proposed solution? And, what were the results? about attrition
The state implemented a data warehouse from Teradata that allowed them to examine data and identify/flag traits that were consistent with fraudulent return. The state prioritized their efforts to go after refund fraud.
What was the solution Maryland adopted?
The company adopted a Tableau system that could be used to store, analyze, and present data for decision making. Because the system was software as a service, SaaS, it required very little in up-front investment. After using the system, the company is able to access and utilize data in ways that it was never able to in the past. They are now able to generate reports as well as answer customer questions with ease.
What was the solution and the obtained results/benefits from Macfarlan Smith?
The firm had begun to work with a BI system from Oracle, but it could not meet the demands being placed on it in terms of stability, speed, and features. AARP was unable to generate the analytics needed to support its activities.
What were the challenges AARP was facing?
The business was facing challenges, and needed to ensure that they had good visibility of the competitive landscape. The company's 15 distinct divisions, each with a different data and IT infrastructure, aggravated this goal.
What were the challenges faced by the large Dutch retailer?
Challenge: The Dallas Cowboys Merchandising Division needed more visibility into their data so they could run more profitably. They selected Microsoft as the baseline platform but was not sufficient for the task.
What were the challenges from Dallas Cowboys?
The first was the changing demographics of car owners. As cars were sold on the secondary market, it was more difficult for them to identify new potential customers.
What were the challenges of SiriusXM? Comment on data-related challenges.
Additionally, the company had a technical challenge because of an acquisition. There was uncertainty about their ability to use all of the technology available through the acquisition.
What were the challenges of SiriusXM? Comment on technology challenges.
The town was seeking an accurate way to track the use of water across multiple locations to both identify potential leaks as well as simplify meter readings.
What were the challenges the Town of Cary, North Carolina was facing?
The state was facing tax fraud from fraudulent returns as other states were, and the process of detecting and investigating potential fraud was time consuming.
What were the challenges the state of Maryland was facing with regard to tax fraud?
Because the customer experience is critical, all customer issues need to be tracked, monitored, and resolved as quickly as possible. But Expedia had no uniform way of measuring satisfaction, of analyzing the drivers of satisfaction, or of determining the impact of satisfaction on the company's profitability or overall business objectives. However, there was plenty of data to work with. It took a business analyst two to three weeks every month to pull and aggregate the data, leaving virtually no time for analysis. Expedia's solution was to start by identifying key drivers of customer satisfaction. From these drivers, the customer satisfaction group constructed a scorecard application. They came up with 10 to 12 objectives that linked directly to Expedia's corporate initiatives, which translated into more than 200 KPIs. This involved three steps: deciding how to measure satisfaction, setting performance targets, and putting the data into context. All of this was applied to their data warehouse (which they called DSS Factory). As a result, managers and executives have a quick and transparent view of how well actions are aligning with the strategy, with the ability to drill down into the data underlying any of the trends or patterns observed. This would have taken weeks to do previously. Other business units are also benefitting.
What were the challenges, the proposed solution, and the obtained results of Expedia.com?
Challenge: The challenge facing BP Lubricants was that it had been involved in merger activity, which meant it had data held in disparate source systems. To be more agile and prepare for growth, it wanted a unified system. So, as a result of merger activity, BP need to integrate data held in disparate source systems without the delay of introducing a standardized ERP system (Enterprise Resource Planning). Solution: The proposed solution was Kalido, an adaptive enterprise data warehousing (EDW) solution. The system integrates and stores information from multiple source systems to provide consolidated views for marketing, sales, and finance. Results: The obtained results are that BIGS helps the business identify a multitude of business opportunities to improve profits and lower costs. Typical benefits include improved consistency and transparency of business data, faster and more flexible reporting, and greater ability to respond intelligently to new business opportunities.
What were the challenges, the proposed solution, and the obtained results with BIGS?
The Scottish pharmaceutical company in the UK had a number of challenges to overcome. The first was data located in many systems, some of which were difficult to access. Another issue was that the quality of the data was in doubt, bringing concerns that results may not be valid. Finally, even with data aggregated and scrubbed, the process of using that data for analysis was very time consuming.
What were the data and reporting related challenges Macfarlan Smith facing?
The company faced both market-driven and technology-driven challenges. The competitive nature of the marketplace made it important for them to always be improving on their products. Technically, the company needed a better method to analyze the large volumes of data that it collected.
What were the main challenges for the medical device company, Instrumentation Laboratory? Were they market or technology driven? Explain.
The company felt that it would be able to maintain a strategic advantage if it began working towards being a data-driven marketing company. This would allow them to more precisely target current and potential customers.
What were the proposed solutions to the challenges of SiriusXm?
The company has been able to progress significantly in its goal of becoming a data-driven marketing organization. With the new systems in place, it is possible to move campaigns faster with better visibility.
What were the results and benefits? Were they worth the effort/investment?
he project has produced positive results. The system is significantly faster, and allows functional employees to easily use and create reports. In the future the system will support more reliance on BI within the enterprise.
What were the results obtained in the short term, and what were the future plans in AARP? T
The results were very positive and, based on the information presented, probably provided a positive return on ROI. Specifically the analytics tools allowed them to maintain regulatory compliance, ensure product consistency, evaluate supply chain issues, and save time overall.
What were the results of Instrumentation Laboratory on trying to fix the challenges? What do you think was the real return on investment (ROI)?
Based on this project, the city has a much better understanding of how water is used within its borders. Additionally, it is much easier to bill for water use and plan for future demands.
What were the results of town cary?
The team was able to flag a smaller number of potentially fraudulent returns, but those that they did identify were significantly more likely to be false. This allowed the state to recover $7 million more, making the investment pay off.
What were the results that Maryland obtained? Did the investment in BI and data warehousing pay off?
Traditional solutions are quite varied. Most are centered on obvious problems, but may not take into account problems that are difficult to evaluate or quantify. Additionally, they may not account for the confluence of multiple problems.
What were the traditional methods to deal with the attrition problem?
Challenge: The company's primary challenge was the variety and diversity in the data that it needed to aggregate. Solution: The company selected a SAS Visual Analytics system to manage and report the data. Result: After implementing the system, the company has been able to deliver quality information in the form of reports much faster and at a lower cost.
What were their challenges, the proposed solution, and the obtained results of Electrabel?
ETL (extract, transform & load) and analysis tools and data warehousing environments.
When these processes are implemented, data can be accessed and made accessible to an array of
Expedia, Inc., is the parent company to some of the world's leading travel companies (hotels.com, hotwire.com, expedia.com). Therefore, it acts as an online travel agent for consumers who want to travel. Because Expedia.com is an online business, the customer's shopping experience is critical to Expedia's revenues. The online shopping experience can make or break an online business. Obviously, the travel experience is also critical to Expedia's success.
Who are the customers for Expedia.com? Why is customer satisfaction a very important part of their business?
TELCOs control the telecommunications infrastructure, and acquire much usage data as a result. They have the technical expertise to create, deploy, and refine plans to address their business challenges. The industry and mobile technology have expanded and improved over the years, which provides a strong foundation on which to build intelligent solutions. The data analytics solutions that have been created to meet these challenges have also improved drastically over the past few years, placing TELCOs in a good position to capitalize on their technological advantages.
Why do you think TELCOs are well suited to take full advantage of data analytics?
Energy companies are typically dealing with a very large amount of information that comes from a wide variety of sources. Additionally, these companies tend to be working with very large budgets, and the ability to identify areas of possible savings can result in large increases to revenue.
Why do you think energy supply companies are among the prime users of information visualization tools?
Revenues are complex and have many sources. This variety and detail make understanding the data difficult, hampering efficiency. The use of BI tools allows for better analysis, understanding, and governance.
Why is it important for IRS and for U.S. state governments to use data warehousing and business intelligence (BI) tools in managing state revenues?
Like a business, a state government can operate more efficiently and make better decisions if it has access to current data. State officials can use the EDW to improve efficiency and better serve the state's residents.
Why would a state invest in a large and expensive IT infrastructure (such as an EDW)?
DMs
are a less-expensive solution that can be replaced by or can supplement a data warehouse.
Ratio data
are commonly found in physical science, such as mass, length, time, but in business, the values for the variable "salary"
Performance dashboards
are commonly used in BPM software suites and BI platforms
Specialized charts
are often derived from the basic charts as exceptional cases.
Linear regression and logistic regression
are the two major regression types in statistics.
Geographic map -
are typically used together with other charts and graphs, as opposed to by themselves, and show postal codes, country names, latitude/longitude, and etc.
Roll Up -
computing all of the data relationships for one or more dimensions
Data marts (DMs)
contain data on one topic (e.g., marketing).
Data quality and data integrity
critical to analytics
Time:
daily, weekly, monthly, quarterly, or yearly
Visualization
differs from traditional charts and graphs in complexity of data sets and use of multiple dimensions and measures.
Management -
displaying operational data that identify what actions to take to resolve a problem.
parallel processing and/or partitioning
enables a data warehouse to handle complex queries and scale up to handle many more requests
Bubble chart -
enhanced variant of a scatter plot because it adds a dimension via the size of the dot
Key performance indicator (KPI)
represents a strategic objective and metrics that measure performance against a goal
data
has become one of the most valuable assets of today's organizations.
the data
has to comply with some basic usability and quality metrics.
Geographic map -
helpful when a data set contains location data; can be used with GIS, geographic info systems.
Hierarchy chart -
helpful when illustrating the hierarchy chart of employees in a company
Statistics
is a collection of mathematical techniques to characterize and interpret data.
Traditional reporting process
is a manual process of collecting and aggregating financial and other information.
Logistics regression
is a probability-based classification algorithm.
A data warehouse (DW)
is a specially constructed data repository where data are organized so that can be easily accessed by end users for several applications.
Data preprocessing
is a tedious, time-demanding, yet crucial task in business analytics.
operational data store (ODS)
is a type of customer-information-file database that is often used as a staging area for a data warehouse.
A business report
is a written document that contains information regarding business matters.
ETL
is an integral process in any data-centric project.
A report
is any communication artifact prepared with the specific intention of conveying information in a presentable form.
Regression, especially linear regression,
is perhaps the most widely known and used analytics technique in statistics.
Visual analytics
is the combination of information visualization and predictive analytics.
data
is the main ingredient for any BI, data science, and business analytics initiative.
Measures:
money, sales volume, head count, inventory profit, actual versus forecast
Drill Down/Up -
navigating among levels of data ranging from the most summarized (up) to the most detailed (down)
Measures
need to have targets that are based on research and reality rather than arbitrary.
PERT chart -
network diagrams; show precedence relationships among the project activities/tasks.
ratio and interval
numerical data types
Operational plan:
plan that translates an organization's strategic objectives and goals into a set of well-defined tactics and initiatives, resource requirements, and expected results for some future time period (usually a year).
Dimensions:
products, salespeople, market segments, business units, geographical locations, distribution channels, country, or industry
Dashboards
provide visual displays of important information that is consolidated and arranged on a single screen so that the information can be digested at a single glance and easily drilled in and further explored.
ETL technologies
pull data from many sources, cleanse them, and load them into a data warehouse.
to improve managerial decisions
purpose of a business report
Data (datum in singular form)
refers to a collection of facts usually obtained as the result of experiments, observations, transactions, or experiences.
BPM
refers to the business processes, methodologies, metrics, and technologies used by enterprises to measure, monitor, and manage business performance.
Interval
scale measurement is temperature on the Celsius scale where the unit of measurement is 1/100 of the difference between the melting temperature and the boiling temperature of water in atmospheric pressure; that is, there is not an absolute zero value.
Measures
should balance the needs of shareholders, employees, partners, suppliers, and other stakeholders.
Measures
should be a mix of past, present, and future.
Measures
should focus on key factors.
Measures
should start at the top and flow down to the bottom.
data from inside and outside the organization (via the use of ETL (extraction, transformation and loading of the data)
source of a business report
Data acquisition , Information generation , Decision making ,Process management
steps of a business report
Linear regression models
suffer from highly restrictive assumptions.
Real-time or active data warehousing
supplements and expands traditional data warehousing, moving into the realm of operational and tactical decision making by loading data in real time and providing data to users for active decision making.
Nominal data
the code values for the variable "marital status", S-single, M-married, D-divorced
Ordinal data
the data field for the variable credit score can be generally categorized as (1) low, (2) medium, or (3) high
Line chart -
to show how donations to United Way Giving Fund have increased over the past five years.
Pie chart -
to show last month's sales by product line for the four products you sell and show which product line sold the greatest proportion of total sales.
Pie chart
to show relative proportions of majors declared by college students in their sophomore year
Pivot -
used to change the dimensional orientation of a report or an ad hoc query-page display
Data , Information (report), Decision , Action
what are the steps to a report?
Hypothesis testing (explanation) Forecasting (prediction)
what can regression be used for?
Success (or mere survival) depends on new projects: creating new products, entering new markets, acquiring new customers (or businesses), or streamlining some process.
what do we need to do differently when we act?