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The system was developed with USSD or SMS technology to be used without limits on all modern or outdated mobile devices. The main objective is to reach the entire population by offering the most comfort possible without complications in technologies in terms of use and their monetary movements. More about this source text. The main operation is to buy your balance at any shipping point and use it at any time sending to anyone and keep your balance without moving so much. Because the thing goes like this: We have to have a main number that answers all the requests of the final client, consulting everything in a database and saving. The main task in the foreground is to get an automated server to receive messages from the subscribers to the system, their requests, and this server simultaneously processes the request for the message by responding to the requester, the requester at the same time confirms his transaction with a pin code According to the transaction, the commissions are charged in your wallet, in the same way there will be users as affiliates where they carry out their operations with their balances and the commissions are distributed between the same and the company according to the established percentage, this event must be registered in a database that will store the customer's information, then this, when made possible, must be a part of the Administration panel, to be able to see all the requests processed, the balances of the clients, their operations, a part to enable or create new clients and users by roles. A confirmation PIN must be sent from the end user, for security reasons, an encrypted PIN. Integrate payment gateway for international clients and they will use VISA to recharge their wallet. -> The user will use their VISA card to recharge their balance if it is what they have and we will have to use a gateway, NOW, nationwide, the use of cards is almost 0%, the second option for natives is: We have to add the option to create ticket and printed or small printed cards to scratch that will contain a code, for example: 1286565XXX, then once scratch and enter it, a balance is recharged, then they will have to be GENERATED with the same More about this source text. system, maintaining referential integrity and printing them. -> Okay, will you buy me scratch cards and give me cash? YES. -> Perfect, in some kiosks installed for example in the streets and commercial places. A well-organized project makes maintenance easy. Error correction. Remember business logic well. There must be a part to configure or parameterize the commissions according to the amounts to be sent. Each user must have their balance account and commissions account, these commissions must be withdrawn at any time and be transferred to their account of movements. If the user asks for a history of their transactions, it is sent to them at the same time as an Excel or PDF file. BUSINESS LOGIC: • Prices of cards to print: 10,000, 25,000, 60,000, 90,000, 125,000, 300,000. • Make the shipment the interest commission is 20% • Receive by saving in the wallet the commission is 20% interest, it is entered into your account • Receive by taking cash the commission of 20% is transferred to the effective payer. • Make payment of a bill for a service with your wallet the standard spending commission is 1,000 • Receive payment of an invoice for a paid service the standard expense commission is 1,000 • Make payment of an article or product the expense commission is 5%. • Receive payment for an item or product, the expense commission is 5%. • Buy GETESA or MUNI balance, the expense commission is 50XAF. CASES: CASE 0: REGISTER: TYPES OF USERS: SUPER_ADMIN, ADMIN, FRANCHISE_CLIETE, NORMAL_CLIENT • Send word: HELLO, respond with an image incorporated wallet + Template; CORPORATED WALLET Greetings. Your shipments, purchases earnings and wallet "You win and I win" Send: R -> Register S -> If you are already registered IF -> More information (Yes, it is the first time). FAMILY (if already registered) A. Reload. • Receive menu descriptions of services: A. Register, B. Send, C. Receive, D. Join to win, E. My balance, F. Extract, G. About us. More about CASES. • Register ok: Credit card code (mandatory), ^ Telephone number (obviously already obtained with the sms), Full name, City, PIN code, Recharge code • Verify account. CASE 1: PERFORM OPERATION: • Send word: FAMILY • Receive menu descriptions of services: AB. Recharge. B. Send, B1. Send payment for a service, C. Receive, C1. Receive service payment. D. Join to win, E. My balance, FA. Pay bills, FB. Pagar luz, F. Extract, G. About us. • Reload: Put scratch card code (purchased at any kiosk or agency) • Receive sms balance. • REFILL WITH VISA CARD: link from stripe or any payment website with OTP • Synchronize the balance of the currency or reloaded currency CASE 2: SEND: • Amount to send • Recipient phone • Balance ok? • Ask for confirmation PIN • Debit sender customer account: amount sent, amount on commission (percentage setting) • Distribute or distribute commissions: company percentage to company commissions account, sender percentage to commissions account. • Complete operation message: Sender, amount, commission, remaining balance, date CASE 3: RECEIVE: Code shipping • Sender • Amount • PIN confirmation • Operation message CASE 4: JOIN TO WIN • Send word: WIN • Request card or recharge code (credit account with higher balance) • Transform to account (FRANQUICIA_CLIETE) • Automatically establish commission percentage for sending or receiving. (SUPER ADMIN PANEL } • Ok: account info message. CASE 5: ACCOUNT INFORMATION • Send word: BALANCE or INFO • Info message: Name, balance, commissions CASE 6: WITHDRAWAL COMMISSIONS • Send keyword: DAME • Amount to withdraw • PIN confirmation • Debit commissions account • Top up main customer account. • Regularize account of commissions. • Status information. CASE 7: CHANGE PIN • Send PIN word • Change? • old PIN • New PIN • new PIN confirmation • PIN message changed successfully CASE 8 FB: PAY LIGHT • SEGESA phone • Counter code • Amount payable • PIN confirmation • Invoice in PDF • Successful payment • Debit 1000 • Automatic collection of the amount of 1000 SEGESA account • Income of the amount paid to the SEGESA account • Ge CASE 9 F: REQUEST EXTRACT • Write word: EX • Dates: Start date, End date, ALL • Excel file with transaction information. CASE 10 G: ABOUT US • Send word: CONTACT • Detailed information on the company's services and contacts. CASE 11: ADMINISTRATIVE PANEL • Statistics of operations and statuses of Chart.js accounts • Admin users • Manage clients • Receive • Send • Operations • Returns • Payments • Links • Accounts • Setting • Generate balances or scratch cards WALLET OPERATIONS. CASE 0-OB: RECEIVE PAYMENT OF A SERVICE. • Keyword: PS C1 • Ask to put amount • Ask to put a pay phone • Ask to put a description • Receive descriptive sms and send payment code automatically • Receive authorized payer code • Confirm transaction code • Apply expense commission CASE 1-OB: Make payment for a service • Receive payment code from provider • Keyword: B1 • Enter code • See payment info. • Q-> Confirm • PIN confirmation • Debit the payer account the amount • Debt account the payer commission expenses • Change transaction status. Beforehand in the future I want to consume a transaction by its code in another application and verify its effectiveness in the future with another application that I have in my fan of projects. It will be a big platform, MY VISION.

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Digiency is All in One Multipurpose Business Website Template. This Template is ideal for Digital agencies, SEO agencies, It Companies, Consulting Companies, Financial Companies, SEO Companies, or any type of business lading page of Figma version Pre-Built blocks premade Layout Components based Bootstrap grid-based Easy to Customize

Software agency full-stack website MERN project, where you will have all kinds of features eCommerce, blog,business

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This is a Responsive quick and easy customisable Modern Multipurpose Webinar booking website Page that comes with Booking page and successful page. This free template offers numerous awesome features for , agency, business, educational, enterpreneur, digital agency, start up business, consulting firms, insurance, loan, tax help, investment firm or your just a lead form.

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Agile consulting: is it right for you? Find out with this one-page quick easy checklist, so you can make the most of your team's time, money, energy, and enthusiam.

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How to share data with a statistician This is a guide for anyone who needs to share data with a statistician or data scientist. The target audiences I have in mind are: Collaborators who need statisticians or data scientists to analyze data for them Students or postdocs in various disciplines looking for consulting advice Junior statistics students whose job it is to collate/clean/wrangle data sets The goals of this guide are to provide some instruction on the best way to share data to avoid the most common pitfalls and sources of delay in the transition from data collection to data analysis. The Leek group works with a large number of collaborators and the number one source of variation in the speed to results is the status of the data when they arrive at the Leek group. Based on my conversations with other statisticians this is true nearly universally. My strong feeling is that statisticians should be able to handle the data in whatever state they arrive. It is important to see the raw data, understand the steps in the processing pipeline, and be able to incorporate hidden sources of variability in one's data analysis. On the other hand, for many data types, the processing steps are well documented and standardized. So the work of converting the data from raw form to directly analyzable form can be performed before calling on a statistician. This can dramatically speed the turnaround time, since the statistician doesn't have to work through all the pre-processing steps first. What you should deliver to the statistician To facilitate the most efficient and timely analysis this is the information you should pass to a statistician: The raw data. A tidy data set A code book describing each variable and its values in the tidy data set. An explicit and exact recipe you used to go from 1 -> 2,3 Let's look at each part of the data package you will transfer. The raw data It is critical that you include the rawest form of the data that you have access to. This ensures that data provenance can be maintained throughout the workflow. Here are some examples of the raw form of data: The strange binary file your measurement machine spits out The unformatted Excel file with 10 worksheets the company you contracted with sent you The complicated JSON data you got from scraping the Twitter API The hand-entered numbers you collected looking through a microscope You know the raw data are in the right format if you: Ran no software on the data Did not modify any of the data values You did not remove any data from the data set You did not summarize the data in any way If you made any modifications of the raw data it is not the raw form of the data. Reporting modified data as raw data is a very common way to slow down the analysis process, since the analyst will often have to do a forensic study of your data to figure out why the raw data looks weird. (Also imagine what would happen if new data arrived?) The tidy data set The general principles of tidy data are laid out by Hadley Wickham in this paper and this video. While both the paper and the video describe tidy data using R, the principles are more generally applicable: Each variable you measure should be in one column Each different observation of that variable should be in a different row There should be one table for each "kind" of variable If you have multiple tables, they should include a column in the table that allows them to be joined or merged While these are the hard and fast rules, there are a number of other things that will make your data set much easier to handle. First is to include a row at the top of each data table/spreadsheet that contains full row names. So if you measured age at diagnosis for patients, you would head that column with the name AgeAtDiagnosis instead of something like ADx or another abbreviation that may be hard for another person to understand. Here is an example of how this would work from genomics. Suppose that for 20 people you have collected gene expression measurements with RNA-sequencing. You have also collected demographic and clinical information about the patients including their age, treatment, and diagnosis. You would have one table/spreadsheet that contains the clinical/demographic information. It would have four columns (patient id, age, treatment, diagnosis) and 21 rows (a row with variable names, then one row for every patient). You would also have one spreadsheet for the summarized genomic data. Usually this type of data is summarized at the level of the number of counts per exon. Suppose you have 100,000 exons, then you would have a table/spreadsheet that had 21 rows (a row for gene names, and one row for each patient) and 100,001 columns (one row for patient ids and one row for each data type). If you are sharing your data with the collaborator in Excel, the tidy data should be in one Excel file per table. They should not have multiple worksheets, no macros should be applied to the data, and no columns/cells should be highlighted. Alternatively share the data in a CSV or TAB-delimited text file. (Beware however that reading CSV files into Excel can sometimes lead to non-reproducible handling of date and time variables.) The code book For almost any data set, the measurements you calculate will need to be described in more detail than you can or should sneak into the spreadsheet. The code book contains this information. At minimum it should contain: Information about the variables (including units!) in the data set not contained in the tidy data Information about the summary choices you made Information about the experimental study design you used In our genomics example, the analyst would want to know what the unit of measurement for each clinical/demographic variable is (age in years, treatment by name/dose, level of diagnosis and how heterogeneous). They would also want to know how you picked the exons you used for summarizing the genomic data (UCSC/Ensembl, etc.). They would also want to know any other information about how you did the data collection/study design. For example, are these the first 20 patients that walked into the clinic? Are they 20 highly selected patients by some characteristic like age? Are they randomized to treatments? A common format for this document is a Word file. There should be a section called "Study design" that has a thorough description of how you collected the data. There is a section called "Code book" that describes each variable and its units. How to code variables When you put variables into a spreadsheet there are several main categories you will run into depending on their data type: Continuous Ordinal Categorical Missing Censored Continuous variables are anything measured on a quantitative scale that could be any fractional number. An example would be something like weight measured in kg. Ordinal data are data that have a fixed, small (< 100) number of levels but are ordered. This could be for example survey responses where the choices are: poor, fair, good. Categorical data are data where there are multiple categories, but they aren't ordered. One example would be sex: male or female. This coding is attractive because it is self-documenting. Missing data are data that are unobserved and you don't know the mechanism. You should code missing values as NA. Censored data are data where you know the missingness mechanism on some level. Common examples are a measurement being below a detection limit or a patient being lost to follow-up. They should also be coded as NA when you don't have the data. But you should also add a new column to your tidy data called, "VariableNameCensored" which should have values of TRUE if censored and FALSE if not. In the code book you should explain why those values are missing. It is absolutely critical to report to the analyst if there is a reason you know about that some of the data are missing. You should also not impute/make up/ throw away missing observations. In general, try to avoid coding categorical or ordinal variables as numbers. When you enter the value for sex in the tidy data, it should be "male" or "female". The ordinal values in the data set should be "poor", "fair", and "good" not 1, 2 ,3. This will avoid potential mixups about which direction effects go and will help identify coding errors. Always encode every piece of information about your observations using text. For example, if you are storing data in Excel and use a form of colored text or cell background formatting to indicate information about an observation ("red variable entries were observed in experiment 1.") then this information will not be exported (and will be lost!) when the data is exported as raw text. Every piece of data should be encoded as actual text that can be exported. The instruction list/script You may have heard this before, but reproducibility is a big deal in computational science. That means, when you submit your paper, the reviewers and the rest of the world should be able to exactly replicate the analyses from raw data all the way to final results. If you are trying to be efficient, you will likely perform some summarization/data analysis steps before the data can be considered tidy. The ideal thing for you to do when performing summarization is to create a computer script (in R, Python, or something else) that takes the raw data as input and produces the tidy data you are sharing as output. You can try running your script a couple of times and see if the code produces the same output. In many cases, the person who collected the data has incentive to make it tidy for a statistician to speed the process of collaboration. They may not know how to code in a scripting language. In that case, what you should provide the statistician is something called pseudocode. It should look something like: Step 1 - take the raw file, run version 3.1.2 of summarize software with parameters a=1, b=2, c=3 Step 2 - run the software separately for each sample Step 3 - take column three of outputfile.out for each sample and that is the corresponding row in the output data set You should also include information about which system (Mac/Windows/Linux) you used the software on and whether you tried it more than once to confirm it gave the same results. Ideally, you will run this by a fellow student/labmate to confirm that they can obtain the same output file you did. What you should expect from the analyst When you turn over a properly tidied data set it dramatically decreases the workload on the statistician. So hopefully they will get back to you much sooner. But most careful statisticians will check your recipe, ask questions about steps you performed, and try to confirm that they can obtain the same tidy data that you did with, at minimum, spot checks. You should then expect from the statistician: An analysis script that performs each of the analyses (not just instructions) The exact computer code they used to run the analysis All output files/figures they generated. This is the information you will use in the supplement to establish reproducibility and precision of your results. Each of the steps in the analysis should be clearly explained and you should ask questions when you don't understand what the analyst did. It is the responsibility of both the statistician and the scientist to understand the statistical analysis. You may not be able to perform the exact analyses without the statistician's code, but you should be able to explain why the statistician performed each step to a labmate/your principal investigator. Contributors Jeff Leek - Wrote the initial version. L. Collado-Torres - Fixed typos, added links. Nick Reich - Added tips on storing data as text. Nick Horton - Minor wording suggestions.

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The "Easy Consulting Master" GitHub repository is a React.js-based project that offers a simple and elegant web interface for a consulting company. The website has several sections, including a homepage, about page, services page, blog page, and contact page.

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Software agency full-stack website MERN project, where you will have all kinds of features eCommerce, blog, business

An easy way to generate the support rota for Unboxed Consulting in wiki markup

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