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The business rules for this case are to keep the "Mary" unless the data show "Mary-Ann". I guess my queries don't affect this.

This is just an example. The rules are to keep only one of the two first names. So, from John, Peter, it will be John. Regarding the second one, it was a typo (so, not "johns" but "john"). I fixed this in my original post.

Hi guys, I know...these are some of the main challenges in data cleansing and thanks for your replies! Clearly, most of the data are single first names like "John" or "Anna". But, there are some records (about 10k) that are more complex. The examples that I gave you are the main ones that I...

Hello, I am trying to clean first names but there is such complexity that I cannot do it in a single query. j. b john john john j j. John john j john, john, peter j, john john j,john In all different examples, I want the output to give me "John". So, I need a query to remove...

Hi... Thanks for replying so quickly. I am afraid that I lack of programming skills. From what I can see, all your suggestions require that. Is there any link that suggests this solution and, so, I can replicate to my case? Alternatively, is there any other (more straightforward) way for...

Hello, I have a problem importing a file with around 3 million records. I get a csv comma delimited file with no quotations from an external source. It contains consumer data with demographics and personal details. However, the address field contains commas (but not all records). This means...

Create another field with the same data and use the replace function in your query e.g. =replace(table!field,"stuffno ","")

Hi Mark, Thanks for the post. Using SQL, what I am getting is this one: ID Month YEAR 44444 1 2013 44444 2 2013 44444 3 2013 44444 5 2014 44444 6 2014 55555 9 2013 55555 10 2013 55555 10 2014 66666 11 2012 How am I supposed to count the consecutive months using distinct ids (like the example...

Hi All, I was wondering if there is someone who can help me out with something here. Ok...We have a retail shop and we want to see for each customer if he had bought at least once a month a specific product consecutively. To see the concept: If he had bought the product let say 2 two times in...

Hello, Is there a function or query that I can split a field into different columns? For example, I have First Name, Last Name, Address. But I want to split the address field into Address1, Address2, Address3, Address4 as the initial Address field has a lot of characters with commas e.g. 11...

It will be a basic question, but can I ask if you included the key field from the table you wanted to update?

Fantastic!!!!!!Your instructions are now very clear. It worked!!!! Thank you so much!!! You saved me a lot of working time!

Yes. Based on your example, suppose the OrderID and OrderDate have 100,000 records from the tblOrder table and the Customer ID from tblCustomer has 30,000 records (these are unique customers). How can I create in this case a table with the unique customers plus new columns with the most recent...

Sorry for the delay. Sorry, I don't understand. How am I suppose to follow that in a simple append query? What will be my criteria? Could you please give me further details? I don't know how to use outer join. Thanks

Hi again, I need help on something else. I have a table with orders (100,000 records) and a table with customers (30,000 records). Consequently, a customer may have made multiple orders. Both tables have a unique id that link them together. My problem is that if I join them with a simple query...

Hi, I have a question about appending or adding simply records. Everyday, I get a database which is cummulative and I have a combined database with 3-4 tables from different sources but they have duplicates (same id, but different on other fields). I keep a specific structure. However, my...

Hello everyone! I am also new here! I noticed that this forum contains many information about Access and I believe that it will be very helpful! Thanks in advance and I hope you can help me with many question that I have. Cheers