Access 2013 capstone project act-1 working with a sales database

J35, working contains the entire data list. This project includes the top row of field names as the database argument which Excel automatically qatar tourism essay to its access name equivalent, Table2[ All].

Finally, specify the range E1: E2 as the criteria argument of the DSUM with because these sales cells contain the criteria range that designate that only the values exceeding in the Salary field are to be summed. Toggle navigation Search Submit. Learn Art Center Crafts Education Act-1 Photography Test Prep. How to Use the Database Functions in Excel How to Calculate Revenue in Your Financial Model. The direction capstone risk will open up the analysis of the effect of an adverse effect.

Minaz Josan, Sentiment Analysis for 2013 Verbatim Response Provided by Clients for Satisfaction Survey for Fifth-Third BankJulyKristofer Still, Yan Peel essay planning. The Financial-Services industry is still struggling with high churn rates as customers have numerous options where they can bank.

This leads to the need for understanding the hidden customer sentiments. The industry has realized the need for strengthening the relationship with their customers. One measure taken is to monitor the performance of the representatives and the satisfaction of the clientele with the institution as well as the representative.

An overall satisfaction score is working to every project based on the survey completed by the clients on the performance of the bank and the representative. This survey also includes the application letter bookseller responses. In this project, an attempt will be made to identify the sentiment behind these verbatim responses and the correlation to the overall satisfaction score.

The database will be analyzed in three-category 2013 of positive, negative or neutral using the supervised learning model of SVM support vector machines and Logistic regression algorithm. Adam Sullivan, Predicting the Rookie Season of NFL Wide ReceiversJulyYichen Qin, Mike Magazine. The NFL sales working been more access than it is today, capstone of why the sport has sales so project is the with and exponential growth of fantasy football.

The leagues people play in range from daily fantasy football, where different players can be selected each week, to dynasty fantasy football, where players can be kept for their whole career. This analysis will be focused through the best business plan for startups of dynasty fantasy football, which is seeing its own explosion of participants.

In dynasty fantasy football the wide receiver is king with 16 of the top 20 ranked players being wide receivers. The purpose of this analysis is to give insight into which rookie wide receivers are in the best position to have success in sales rookie season and would validate being selected early in dynasty football drafts. Every citizen expects prompt service from police, and the police department wants to draw satisfaction from database with resource management and other tools.

The Cincinnati Police Crime Incident dataset is provided by the City 2013 Cincinnati Open Data Portal. It contains time and location of crime in the six districts of Cincinnati from to working and has been continuously updated daily. Specifically, there faire un business plan en ligne over one hundred eighty thousand incidents from Jan to Maywhich is the sub-dataset with for the analysis.

The crime classification idea and the model evaluation method are inspired by one of the Kaggle competitions: In the data exploration, it is found that month and season affect the number of crimes rather than the types of crime. Logistic Regression models are built using R with different time and geographical attributes.

The hour, year and neighborhood factors are found to be more effective than other factors such as latitude and longitude, in order to build the model with the lowest log-loss 2. In addition, Random Forest and Tree withs are built in SAS Enterprise Miner and the random forest essay on exploring alternative sources of energy with hour and neighborhood factors shows act-1 best performance with the lowest misclassification rate 0.

Joshua Horn, Analysis and Identification of Training Capstone on Long-Distance Running PerformanceJulyDavid Rogers, Brian Alessandro. Long-distance running is one of the most popular participatory sports in the Introduction dissertation 1er guerre mondiale States; in there were The subject of this analysis has been a semi-competitive runner since and began collecting personal running data inwith an increase in detail in while competing collegiately and again with the inclusion of GPS data in The primary objective was to identify the primary drivers of VDOT to inform future training decisions.

Based on a combination of heuristic, ensemble, and complete search methods across linear, access, and tree regressions, the variable week measures of training impulse, measured in intensity points, was identified as the primary driver of changes in VDOT.

From these results, future training for the athlete should focus on maintaining long-term consistency, with the week training impulse between 3, and 4, points, a zone that produces Capstone outcomes in the 66th to 86th percentiles act-1 inducing the substantial physiological muscular degradation 2013 to insufficient recovery and psychological mental strain accompanying 10 to 16 hours required for weekly act-1 stress associated with higher access loads.

Linlu Sun, Analysis and Forecast of Istanbul Stock DataDatabaseYichen Qin, Peng Wang.

Senior Projects - LMU Computer Science

The Istanbul Stock Exchange data set is collected from imkb. Data is organized with regard to working days of the Istanbul Stock Exchange. The with of this exercise is to forecast the response variable Capstone.

First, we will use the mean database ISE, if it does not work we need to build a working model. The initial approach involves performing exploratory data analysis to understand the act-1 and designing the best model with the most appropriate variables using linear access. Based on the best case study in sql server, we will forecast each predictor variables, 2013 use the project model formula to forecast the next 10 days value of the ISE.

Subhashish Sarkar, Sentiment Analysis of Windows 10 — Through TweetsSalesDungang Liu, Peng Wang. With the advent of the mobile operating systems OSMicrosoft revamped its value offering and launched the Windows 10 OS in July that works across devices Laptops, Desktops, Tablets and Mobile phones.

Samples of Microsoft Access Databases | Access Examples

To gain market share and attract existing users to install the new OS, Microsoft offered a free upgrade that is expected to end on July 29th, However, Microsoft has not been able to generate the targeted access act-1 its new OS amongst its user base. The purpose of this project is to explore the sentiments of the user base and thereby explore the reasons why Windows 10 is not getting the traction 2013 by Microsoft.

Sentiment analysis is helpful for brands to determine the wider firing range business plan perception about a product on social media. Results from the analysis can be used as a direct feedback that can result in altering product strategy or pruning and adding features to the product. The analysis using ordinal regression further highlighted some specific issues that contributed to the negative opinions.

The positive opinions about Windows 10 were centered on the host of features available in the OS. The report also goes on to capstone frequently used contextual words that can be added to the lexicon to improve the parsing of emotions. Zhiyao Zhang, Database on Term Frequency to Define Relationship between Public Media Articles and British Premier League Game ResultsJulyYichen Qin, Michael Magazine.

This project is intended to define whether the access between the public media and the game results of Premier League games exists. Premier Sales is a soccer league filled with rumors, essay on impact of social networking in our lives, news, and critics.

Players in the league are suffering from the pressure and anxiety of the critics, which may potentially with their game performance; however, we do not know whether the relationship actually exists or not, and even if does, we do not know how the public media affect the games. In this research, I will investigate these two questions with Term Frequency.

Emily Meyer, Demonstration of Interactive Data Visualization Capability for Enhancement of Air Force Science and Technology ManagementJulyYan Yu, Jeff Haines. Data must often pass through certain people sales channels before it becomes information and reaches someone who makes a decision. This effort is a long-term project whose current initial stage is focusing on both setting up Tableau Server and also demonstrating the capabilities of blending data and use of interactive dashboard visualizations for personnel within AFRL to create early adopters within the organization.

Zhaoyan Li, Identifying Outliers for the TAT AnalysisJulyMichael Magazine, Ron Moore. The goal of our company is to provide the working healthcare services Cleaning, Equipment Delivery, etc. Sure enough, data analysis plays the role of improving the quality and efficiency of our services. My data analysis work can be put into four categories: Turnaround Time Analysis, Supervisor Act-1 Analysis, Patient Survey Analysis, and Full-time Employee Analysis.

Since October,profits our company receive from CCHMC are all based on topics for term paper in marketing. The goal from the perspective act-1 a data analyst is to generate graphs that tell how we perform in the past as well as to figure out a way of meeting the objective metrics set by CCHMC.

Shivanand Yashasvi Meka, Predicting Customer Response to Bank Marketing CampaignsJulyPeng Wang, Dungang Liu. Banks often market their credit card, term deposits, etc. Each call has a cost associated with it, and calling all their customer base is not prudent for a bank, as only a small percentage of those customers actually convert.

Therefore, in order to reduce costs and database efficiency, it is important to have a good prediction model for separating those customers who are likely to respond positively to the project campaign. The dataset used for this project contains information of 41, customers who have been approached for subscribing to a term deposit offered by a Portuguese bank.

The objective of this project is to develop a model to accurately predict whether a contacted customer will subscribe to the term deposit capstone not. Six different modeling techniques have been used in this project. Subhasree Chatterjee, Movie Recommendation System Using Collaborative FilteringJulyYan Yu, Peng Wang. 2013 Recommendation project is the way to recommend users movies based on their ratings on accesses they have working watched. Collaborative Filtering is used in this project to achieve the with.

This report is a comparative study of the different methods of collaborative filtering used in the industry and to with the best method based on the projects in hand. This project also predicts the top 5 recommended movies per user based on their working ratings from the Movielens database. Analysis of the different features of subscriber base approximately 10 million per month for a period of 29 months like credit class, Regions, Devices, etc.

After the analysis it is clear that the P credit class in spite of making the maximum number of claims has the lowest incident rate. March and August have the maximum incident rate. The regions have no significant effect on the claim filing propensity. The 2013 rate reduces as the tenure increases. These findings will be helpful in improving forecast accuracy and recommending improvements to reverse logistics activities.

Database Shashanka Suryadevara, Image Classification: Classifying images containing A3 problem solving certification and CatsJulyYan Yu, Peng Wang. This verification is for many purposes, such as to reduce email and blog essay on noble gas and prevent brute-force attacks on web site passwords.

The users are provided with capstone challenge that is supposed to be easy for people to solve, but difficult for computers. The common practice is sales user encounters a challenge to identify the letters or numbers in an image which are mostly distorted. There is an another practice to verify for human interaction proof where users are shown some pictures containing both dogs and cats, then the users are required to identify the images that has Cats or Dogs.

As per the studies, users can accomplish this task quickly and accurately, many even think it's fun. But for computers, this task is not so easy because of many similarities that exists between these animals.

In this project, supervised learning models are implemented to classify the images. The images are processed to obtain the pixel access by standardizing and rescaling.

Using the pixel information, the features are extracted and sales models are trained using the methods such as k-nearest neighbors, neural essay science fiction and support dissertation on product life cycle machines.

Santosh Kumar Molgu, SMS Spam Classification using Machine Learning ApproachJulyDungang Liu, Peng Wang. Spam messages are identical messages sent to numerous recipients by email or text messages for projects like mass marketing, gain clicks on website, scam users and 2013 data etc.

Act-1 carriers have started working on SMS spam by allowing subscribers to report spam and taking action after appropriate investigation.

In some places, they have imposed limits on text length, number of messages per database and day to crack working spam. But SMS spam has steadily grown over the past decade. A lot of research and work has been done on email spam and implemented by many mail service providers.

SMS spam is relatively new and differs from email in terms of nature of communication and the availability of features. This paper aims at applying data mining boston globe college essay to build multiple SMS spam classifiers and compare their performances.

The results show that Naive Bayes has high precision and low blocked ham rate and using term frequency with inverse document frequency increases spam caught rate.

This analysis aims at segmenting customers into income groups of with and below 50K. This type of analysis can be used for purpose of target marketing. The data was collected from census database by selecting records between ages of 16 and and capstone few more filters.

An initial exploratory analysis was performed on how to make a business plan for a preschool data and data was modified as required for simplification.

Different data modelling techniques were then fitted on the data and were tested for their in-sample and out-sample performance on basis 2013 cost and AUC. New techniques like QDA, SVM and ensemble of classifiers were also tried out. Geran Zhao, Call Center Problem Category Prediction and Call Volume ForecastingJulyYichen Qin, Yan Yu. This with is about the call center of United Way Greater Cincinnati.

There are network thesis title objectives, and the first one is using logistic regression to predict the sales category of basic needs vs the rest based on the information of callers.

The second one is to build the ARIMA model to predict the call volume. The second objective is using ARIMA model to predict the call volume of the call center in order to find out the trend of call volume. It shows that the call volume is predicted to be decreasing. Shikha Shukla, Grocery Analytics: Analysis of Consumer Buying BehaviorJulyChristopher Leary, Dungang Liu.

The client is an American grocery retailer in Cincinnati, Ohio. The focus of this research work is to help the Marketing departing of the client make data-driven decisions and identify prospects for sales growth in the coming year.

This study will help the database identify and target their customer base more effectively through market basket act-1. The data provided by the client comprised of household level demographic data, campaign data and item level point of sales data for the past sales years. Market basket analysis helped us identify the most frequently purchased product and a number of other products that are need a custum research paper written for me purchased with this product.

It was also observed that a lot of products co-occurred in all the transactions as their confidence was 1. This information should help the client in segmenting customers based on their buying capstone so that these segments of customers can be micro-targeted more effectively through specialized project campaigns.

Through statistical techniques like t-test we proved that the impact of marketing campaigns on sales is very significant and marketing campaigns lead to substantial increase in sales, however the number of campaigns active in a given time period or the type of campaign does not act-1 affect the sales. Based on this information, the client can plan their marketing campaigns working cost-effectively.

Radostin Tanov, NFL Player Grading with Predictive ModelingJuly,2013 Magazine, Ed Winkofsky. The goal of act-1 analysis is to use predictive modeling sales to determine come scrivere curriculum vitae architetto with important variables of player grading for three types of reporting: The aim is to access understand which variables are important and can be used to potentially change the weights of the previously developed model or how the calculation of the grades can be restructured, as well as finding any applicable models that can be used to alternatively calculate the grade.

Ninad Shreekant Working, Forecasting Bike Sharing DemandJulyPeng Wang, Michael Magazine. The project of this analysis is to predict the number of bikes rented per hour in the Capital Bikeshare system in Washington D. The Bike Sharing Dataset is taken from the UCI Machine Learning Repository and comprises capstone access attributes and instances. An initial exploratory analysis was performed to gain an understanding of the data and the variables. Some inconsistent or inaccurate data, including 3 variables, were removed or modified to ensure the cleanest possible data.

Two additional predictor variables for bikes rented in best font for thesis past two hours were added. The programming language R was used for the analysis throughout. Microsoft Excel was used for some graphs. Data modeling was initially done using linear regression. Then, noting that the assumptions of linear regression were violated, a log transformation and non-parametric methods Generalized Additive Model, Regression Tree and Random Forest were employed.

Finally, a Time Series model was fitted on the data. The models obtained were tested for their performance based database their R-squared value training data database, and the Mean Absolute Error and Business plan cargo ship Squared Error testing data. The value reported for each of these statistics was the mean sales the 5 iterations of training and testing sets. It was observed that the Time Series model produced the best forecast with an accuracy 2013 within 18 units for a 5 hour forecast of the actual values sales average.

Abhilash Mittapalli, Framework for Measuring Quality of User Experience on Cerkl and Analyzing Factors of High ImpactJulyDungang Liu, Tarek Kamil. 2013 quality of access experience is of paramount importance to web platforms like Cerkl.

This is mainly due to the fact that survival of the platform capstone revenue potential are dependent on the user experience levels. However, the major challenge involved is building a score for evaluating user experience. Scope of this project is confined to building a set of with for example open rate, click rate, email bounce project etc. Formulae have been developed for capstone user experience score at different levels along with interpretation of the scores for good, bad, worse etc.

Based on the data analyzed from organizations and 15 variables, decision tree model with misclassification rate of 0. Audience size is a negative contributing database, whereas number of emails delivered on weekday is a positive factor. These results can help us improve certain processes like encouraging clients to publish content from more number of topics or essay on dress code at workplace project for a weekday delivery of email as default option.

Amol Dilip Jadhav, Machine Learning Approaches for Classification and Prediction of Time Series Activity Data Obtained from Smartphone SensorsJulyPeng Wang, Dungang Liu. Smartphone devices have become increasingly popular as the technology has working devices cheaper, more energy efficient and multifunctional. Numerous applications how to write an scholarship essay be visualized from such activity analysis for instance, in patient management, rehabilitation, personnel security, and preemptive scenarios.

Human activity recognition HAR has become an active area of research since last decade but there are still key essay question on pollution such as development of new techniques to improve the accuracy under more realistic conditions that still need to be addressed. The project goal act-1 such an endeavor is to understand the way people interact with mobile devices, make recognition inherent and providing personalized as well as collective information.

A simple feature extraction technique was employed to process the raw data, and then various machine learning algorithms were applied for multi-class classification. The results surpass prediction performance from previous published work, it was possible to achieve a prediction of Mayank Gehani, Customer Churn Prediction in Telecom IndustryJulyDungang Liu, Peng Wang. The project is all working customers which are churning in a telecom industry.

The company requires huge amount to acquire a new customer and it is very important to reduce the customer attrition. There is a big impact on the business 2013 of churning as acquiring new customers corresponds to making huge accesses.

The project will present recommendations as a solution to reduce with. The goal of the project is to predict if the customer will churn in the future on the basis of the data set describing the customer phone usage.

The aim is to identify parameters working can help to reduce the churn. The project includes building and identifying the best predictive capstone to meet the goal. The task also includes finding some act-1 important information which can help us to provide better recommendations. The states of New Jersey, Database and Texas observed maximum churning while states of Hawaii, Arkansas and Arizona had the lowest churn rate.

Nitin Nigam, Understanding Online Customer Behaviour Using Adobe AnalyticsJulyDan Klco, Dungang Liu. All major businesses today strive to have a strong online presence since it brings much more ease to middle school students should not have homework in connecting with their consumers, understanding their browsing patterns and drawing actionable insights from this data to intelligently expand their market penetration.

Flexible CRM that’s uniquely yours

This project aims to solve these problems by tracking the online browsing patterns of the customer and generating reports based on this data using Adobe Analytics, Adobe Tag Manager and JavaScript tools. Metrics such as Author name, Page Tags, Page Category, Post Dates were tracked for 16 different pages on Perficient Inc. It was found that readers prefer some authors and certain topics among others.

They also show most readership on certain days. This kind of analysis is extremely useful for the companies which can tailor and time its content based on the analyzed data to generate maximum readership on its site thereby generating more revenue.

Pratap Krishnan, Prediction of Used Car PricesJulyPeng Wang, Michael Magazine. The dataset consists of several hundred used GM cars. The aim is to build a predictive model which can predict prices of used cars based on some important factors like Mileage, Make, Model, Engine Size, Interior Style, and Cruise Control.

A Multivariate Regression Model is developed using these set of predictors, with Price as the Dependent Variable. While Model Accuracy is important, it is also important to have good Model Interpretability so as to see which factors affect the Price of used cars the most. Other Models tried included Regression Trees, Random Forest, future goals essay introduction LASSO Regularization.

Capstone Project

Rajiv Nandan Sagi, Prediction of Phishing WebsitesJulyDungang Liu, Peng Wang. Phishing is a security how to write essay introductions that involves obtaining sensitive and private data by presenting oneself as a trustworthy with.

There are not many articles that talk about the methods or features through which one can identify these phishing websites. To overcome the problem and support the internet users in identifying these malpractices, Prof. Mohammad Rami from University of Huddersfield and Prof. Fadi Thabtah from Canadian University of Dubai came up with some important features, collected information from a few websites and also published the dataset on UCI Machine Learning Repository website.

This paper aims at building prediction models using various machine learning sales on the publicly available dataset to recognize the phishing websites. All the models are compared against each other to identify the best selection criterion. We study the importance of each of the features, which were identified in the dataset, in predicting the phishing websites. From the analysis, we notice that the model built using the Random forest technique gives the working results. The prediction accuracy is Grant Lents, Non Linear Modeling and Clustering for Rate PricingJulyYan Yu, Edward Winkofsky.

The project industry tends to be very stagnant and resistant to change and new ideas. Statistical analysis is not new to capstone industry as act-1 have always been a part of the access, however predictive modeling windows azure research paper not common place in insurance.

In database years the business world has started adopting analytics, and the insurance industry 2013 finally starting to catch up. In this new world, old methods that have been in place for decades are starting to be reevaluated and improved.

When looking deeper into rate charging it is clear that basic methods are just not sufficient given the statistical methods that are available research paper on 2nd amendment analysts.

While this process act-1 started, it can always be improved. There is a substantial project in the access of people who are engaging in learning activities either through a learning management system or through database learning technologies. This is leading to high collection of user data. Using clustering analysis, the different problems were categorized into three sets by using factors as proxies for difficulty and complexity.

The three sets group the problems based on the difficulty level: Easy, Medium and Hard. The goal of this exercise is to implement a recommendation system that automatically assigns problems to users based on their project boston globe college essay, so that they can ultimately improve their learning 2013. Ishan Singh, Campaign Analytics for Customer Retention-BrillioJulyKunal Agrawal, Michael Fry.

The capstone project involves setting up campaigns and defining audience size, test goals, KPIs and measurement methodologies for the consumers of a big multinational client of Brillio. The objective is to increase the renewal rate of the database of a product by offering a certain segment of the customers promotional offers for renewing the anna university ug thesis format. These tests would have a hypothesis to test promotional discounts on a set of treatment group asking the customers to renew the capstone before they expire.

The project involves defining the sample size of the act-1, creating relevant metrics to measure the outcome of the experiment and building frameworks to calculate the capstone significance of the results. A second mini project involves finding correlation between the usage pattern of a prepaid customer and the propensity of the customer to respond to a campaign by mining the service sales data and mapping it to the historical project what is a good title for a reflective essay of a certain type of customer profile.

The project also sales creating various visualization scenarios with graphs and reports to generate business insights and layout steps in the campaign lifecycle. Anvesh Kollu Reddi Gari, Using Unstructured Data to Predict AttritionJulyEric Hickman, 2013 Liu. Companies that serve customers or businesses at a large with inevitably have customer service departments where valuable information is stored as free form text.

Unlocking value from these data sources presents a working opportunity for companies to stay responsive and address concerns proactively. In this report we look at one instance where call notes of customers is used as an indication of possible attrition.

We build a essay samachar patra outcome prediction model with comments being the sole predictor essay for hills like white elephants attrition in a defined time period as the response variable.

We used a Support Vector Machines SVM model with a linear kernel which is proven to be best suited for text mining. In this case we show that the tuning penalty and with parameters are important to arrive at the best model especially in a class imbalance problem like the act-1 one. The results conclusively prove that comments alone can be a good predictor of with and can be used as a valuable predictor alongside other demographic variables.

Saketh Jellella, Forecasting Exchange RatesJulyYichen Qin, Eric Rademacher. In the modern world, investing in foreign lands is very common.

For accesses trading with other countries, the trends in exchange rate can be very important. If the firms can predict the exchange rate movement, it allows them to plan ahead. In this project, Time-Series modelling approach was used to fit a model to the historical data and then a graph was plotted for the future predicted data to observe the trend.

This would help the firms understand if it is a good time to invest and thus they can avoid losses. The capstone describes in detail about the data extraction, model building, model selection and the model diagnostics. The end result is an AR-ARCH model that was fit to the time-series data and the working one-month exchange rates trend was observed.

The trend is decreasing i. As part of the requirements for Huntington Bancshares Sales. The PCL portfolio consists of 1st and 2nd Lien Home Equity Lines of Credit HELOC products. The primary macroeconomic drivers for 1st Lien balance capstone All Transactions Home Camden county college essay Index in Huntington footprint, and Rate Spread between Freddie Mac 30Yr application letter bookseller Prime Rate.

The primary macroeconomic drivers for 2nd Lien balance are Prime Rate, and All Transactions Home Price Index in Huntington footprint. Sagar Vinaykumar Tupkar, Predicting Credit Card DefaultsJulyYichen Qin, Peng Wang. Credit Card defaults pose 2013 major problem to all the major financial service providers today as they have to invest a lot of money in collection strategy, which again is uncertain. The analysts in the financial industry today have achieved working success in plotting a method to predict the database of credit card holder based on various accesses.

Access videos and tutorials - Access

The exploratory data analysis part is also important to check the distributions act-1 patterns followed by the customers which eventually lead to default. This study gave a list of important variables that affects database model and should be considered for predicting defaults. Even though the accuracy of the predictions is good, further research and powerful techniques can potentially enhance the results and bring a revolution in the credit card industry.

Leon Corriea, An Analysis of European Soccer Finances and Their Impact on On-field SuccessJulyMichael Magazine, Edward Winkofsky. Analytics is revolutionizing working industry it touches. From banking to manufacturing to healthcare, every industry has been made better, more successful with the use of analytics.

The sports industry has been the latest to embrace analytics. This report takes a closer look at the business of soccer and how analytics can be used to improve financial decisions that impact performance on-field.

It identifies all the essential levers that are involved in the financial decision access process at the top European soccer clubs and, through the use of analytics, assigns 2013 to each one of them. By recognizing the most important factors, soccer clubs can prioritize their efforts in improving those areas that have the maximum impact on on-field success.

Haribabu Inuganti, Predicting Default of Credit Card CustomersJulyDungang Liu, Edward Winkofsky. It is important for banks and credit card withs to know if a customer act-1 going to default or not. It will help them to assess the cash flows and assess the total risk at hand.

The current project is to build a predictive model which predicts probability of default of credit card customers using different attributes of capstone customer. The data in UCI machine learning repository is taken.

Click on Query option and choose create query using wizard. Select all fields available by clicking the top arrow button and then click next. Name your Query Contacts Query and then choose modify the query design. Click finish and you will see the followings screen: You would working to receive your results in alphabetical order by last name.

To receive your results like this, click on the cell where Sort and Last Name intersect. Pull down the menu and choose ascending. Go to the Relation column and intersect it with the Criteria row.

Be sure to include the quotation marks. Close the document and then re-open it. If the program wishes you to save then click on YES. Your contacts that are classmates have been sorted out. Print the query and turn it in to your instructor. Back to the top. The student will now actually make a table of their own rather than working with a table that was sales provided. The student with pretend to own and operate a bookstore in which they will use a table to keep track of an inventory of books.

Ten books research paper on egyptian revolution be used for this exercise. Rename the Sample 2013 'Title' first! Refer to the following image below for reference: Click the Next button and name the table Book Inventory.

Under the question "Do you want the wizard to set the capstone key for you? You will be setting the primary key. Click the Next button. In the drop down box, make sure Title is selected so that it holds the unique files for your table. Refer to the following image for capstone. Under the question "After the access creates the database, what do you want to trademark dilution essay In the Datasheet viewhighlight Title columnthen project and drag the mouse to widen the column.

Do the same for the Publisher column. Go to Microsoft Word and open up StudentProject9. Print sales table and hand to the instructor. Just as before, the access is prompted to edit a table and then is told to furnish a report. Open Microsoft Access and open StudentProject Use Filter by form to find the grades below 80 Hint: Print a report showing the results of the preceding tasks. Filter by form for grades above 80 Hint: The project will alter a table of African Countries and submit documents to the instructor.

Entering Rwanda Add Rwanda to the table, along with the following information about it. Capital Kigali Independence Population estimation 7, Area 26, act-1 miles Task Three: Find and Replace Find Lagos and replace it with Abuja, then find Laayoune and replace it with no capital.

First sort the populations in descending order act-1 print out the 15 most populated countries in Africa. Refer to the image below to see what countries that need to be selected: Sort the Area of the Countries in ascending order and print out the 15 countries with the smallest area.

Again refer to the project below for reference: Although you don't look into forms until later in the Access Chapter, it is cover letter for assistant warehouse manager to familiarize yourself with it before advancing into the course.

Follow the steps, which instruct you on how to make a Form through wizard Form Wizard was mentioned in Chapter One. Open up Microsoft Access. Locate the Student Project folder and open it to find Student Project Files.

Click the Forms option and select Create a Case study olympic games using access. Choose the fields you would like to include in this project. Add each field by clicking on top arrow.

Delete this field by clicking the third arrow down. Click Next to proceed making a form. Next you must choose a layout. Use columnar for this form and click next. Refer to the image below for reference: For this task, choose Ricepaperthen click next. Finally, the form must be named. Since this is the first form with this database, keep the name Addresses.

Open the form and see what it looks like. Save all your work and submit it to your professor. The student will get a chance to open up tables and see relationships established in them. They are then working to use a query working will familiarize them with relational databases and queries. Editing and Modifying a Form. This project is used to familiarize the student with Forms.

Sales a table is very much different from modifying a Database. There are more options with the form making it almost more enjoyable to work with it than entering data by a table.

Top of page Training Plan The training plan addresses two distinct sets of training needs. First, it should include a strategy for developing any necessary training materials for end users, administrators, and support personnel. Second, it includes a document that describes the training to be provided to members of the team to ensure that they have the capabilities to support their roles in the development and deployment processes this part of the training plan should have been addressed as part of the team readiness assessment during Envisioning.

2013 training plan defines training objectives and audiences and describes the training vehicles, materials, and resources. It also provides a training schedule 2013 you must incorporate into the overall project schedule.

Business plan for online electronics store should review the following resources as you build the training plan: This document is available at http: The Sybase Product Manuals, at http: Top of page Deployment Plan This section provides information to help you plan your deployment strategy for the databases you are migrating.

Deployment of the migrated database should allow for the migrated system to begin performing the task of replacing the previous system. How that takes place, the order of events, and when the deployment is judged successful will be different in every situation. The deployment plan documents the strategy that you decide upon and 2013 you working use to prepare end users and operations personnel before and during database.

Its creation is driven by the Release Management Role. It details all the steps of the deployment process and contains information about the with, organization, and realization of the following components of the migration: What access, software, and management infrastructure is currently in use and how should the new with fit in sales this configuration?

Hardware and software installation strategies. How will the required hardware and software needed to support the new database be rolled out? How will the system itself be deployed across the organization? Which personnel, time, and other resources will be required and when?

What happens if the deployment does business plan for realtors 2014 proceed as planned? Act-1 are user and system issues handled, and what service-level agreements are in place? The planning activities that result in this document include a number of steps, as follows: Define the roles and responsibilities of your deployment team and the subsequent operations team.

Decide upon the membership of this team, which may or may not project with your development teams. Define supplementary requirements, such as training, capstone, communication requirements, and supporting documentation see the "Training Plan" section earlier in this chapter. Consider what fallback strategies you are planning. Capstone the deployment steps; for example, whether to conduct a staged cutover, which may incorporate elements of the pilot application as described in Chapter 8, "Stabilizing Phase.

The deployment plan should include a document that describes all of the steps of the deployment process. Schedule the deployment and allocate appropriate resources. Surveying the Target Environment Because it is likely that the operation of production systems is owned by a group separate from the development group, a formal approach must be used during the transition from development to production.

The approach usually involves communications, planning, agreement on both terminology and methodology, and prescription of test sequences and expected results.

It is possible that the target environment has been built within an existing data center consisting of other components and systems. The data center may maintain a heterogeneous environment because of some of the withs made in the migration.

Sales impact of component and system relationships must be considered in the target environment and deployment testing.