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How to use javascript to identify a customer with no signon


How to use javascript to identify a customer with no signon

By : Rani Kalla
Date : November 17 2020, 01:00 AM
like below fixes the issue Cookies are commonly used for this.
If you only need to access this data client-side, consider using localstorage.
code :


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SharePoint Provider Hosted App - Identify Customer

SharePoint Provider Hosted App - Identify Customer


By : Gheorghe
Date : March 29 2020, 07:55 AM
Does that help Alright, I figured it out. The TenantId is unique for every Office 365 instance as well for on premise.
If anybody interested. here is a piece of code to get the tenant id:
code :
 SharePointContext spContext = SharePointContextProvider.Current.GetSharePointContext(HttpContext);

 Uri sharepointUrl = new Uri(spContext.SPHostUrl.AbsoluteUri.ToString());

 string tId = TokenHelper.GetRealmFromTargetUrl(sharepointUrl).ToString();
Eloqua Cloud App - identify a customer

Eloqua Cloud App - identify a customer


By : justphpin
Date : March 29 2020, 07:55 AM
I wish this help you You can use the following parameters in the Install url of your app to get user and site information from Eloqua:
{SiteName} {SiteId} {UserName} {UserId}
How to identify customer with stripe webhook in Python/Flask

How to identify customer with stripe webhook in Python/Flask


By : Abubakar Sow
Date : March 29 2020, 07:55 AM
I want to generate token(customer ID) with a Letter for identify customers

I want to generate token(customer ID) with a Letter for identify customers


By : MarkM
Date : March 29 2020, 07:55 AM
it fixes the issue I guess you want to generate a random unique id , well, then , make use of the Guid class :
code :
  Dim newId = Guid.NewGuid().ToString

  '''Or you can create required length integer

   Dim ran as New Random
   Dim newId as String = ran.Next(0, 9999999999).ToString("D10") '''this will generate a 10 digit unique ID
  '''Must create a table with the following query :

   CREATE TABLE dbo.tblUsers
   (ID INT IDENTITY(1,1) NOT NULL PRIMARY KEY CLUSTERED,
   UniqueID AS 'UID' + RIGHT('00000000' + CAST(ID AS VARCHAR(8)), 8) PERSISTED,
    Column2...........
    )
Public class abc()
Private Const allchars As String = "abcdefghijklmnopqrstuvwxyz0123456789"
Private Shared random As New Random()
Private sub GenerateId()

Dim builder = New StringBuilder()
For i = 0 To 5
    Dim c = allchars(random.[Next](0, allchars.Length))
    builder.Append(c)
Next
Dim NewId = builder.ToString()
End sub
Is there an efficient strategy for doing a fuzzy join on customer data to identify a single customer ID in R?

Is there an efficient strategy for doing a fuzzy join on customer data to identify a single customer ID in R?


By : lazycat
Date : March 29 2020, 07:55 AM
hop of those help? Before getting to the process of finding duplicates it is important to get/gather good data to begin with.
You have mentioned first name, last name, email and phone number. First names are good, since they usually don’t change unlike email addresses and phone numbers. Last names can change through marriage/divorce. Therefore, it is always good to have other time-invariant variables such as “date of birth” or “place of birth”.
code :
# the head() of my data
test_data <- structure(list(first_name = c("Gabriel", "Roscoe", "Will", "Francyne", 
"Giorgi", "Dulcinea"), last_name = c("Jeandeau", "Chmiel", "Tuckwell", 
"Vaggers", "Fairnie", "Tommis"), date_of_birth = structure(c(9161, 
4150, 2557, 9437, -884, -4489), class = "Date")), row.names = c(NA, 
-6L), class = c("tbl_df", "tbl", "data.frame"))
library(dplyr)
library(tidyr)
library(ggplot2)
library(purrr)
library(stringdist)

# customized stringdistmatrix function
str_dist_mtx <- function(df, x, string_dist, n) {

  temp_mtx = stringdistmatrix(df[[x]],df[[x]])

  temp_tbl = tibble(name1 = rep(df[[x]], each = n),
                    name2 = rep(df[[x]], times = n),
                    str_dist = as.vector(temp_mtx)) %>% 
             filter(str_dist > 0 & str_dist < string_dist) 

  temp_tbl[!duplicated(data.frame(t(apply(temp_tbl,1,sort)))),]

}

# dplyr pipe doing the job
test_data2 <- test_data %>%
                mutate(name = paste0(last_name, first_name)) %>% 
                arrange(name) %>%
                mutate(slice_id = row_number(),
                      slice_id = cut_width(slice_id, 50, center = 25)) %>% 
                nest(-slice_id) %>% 
                mutate(str_mtx = map(data,
                                     ~ str_dist_mtx(., "name", string_dist = 6, n = 50))) %>% 
                select(str_mtx) %>% 
                unnest() 
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