I have 500 Excel documents. I want users to keep working as if that was excel (I'll provide app for that) yet cross-reference data in-between that documents. What database can feet such needs?
So, if i get it ok then you need to get data from ~500 excel files while people may access and change them in real time! I can think of 4 ways of approach:
live links of all files to 1 workbook... hurts me to even think the maintenance and setting ... but it will be "live".
powerQuery: group them all in one data table using PowerQueries or PowerBI or similar, then load them on workbook OR save as csv... 1 button refresh, relatively quick, no actual coding needed
use VBA: access all files (or changed ones...) and get what you want, when you want it. If implemented expertly will only take a few seconds for full scan in modern pc, yet needs someone good at coding VBA.
setup 1) using VBA instead of manually, then using VBA to check for errors etc. Result will be "live" but requires again serious VBA coding...
I believe that 2) is the easiest choice with good maintenance features, ease of setting and good speed... (start in excel ...Data / new Query/from File/from Folder ...)
I have a mainframe application that is called sunet, here are some records.
I want to extract data in excel using vba macros. I have tried by my own but i have no idea how to make connection between mainframe and excel. Please advise me how to do this.
Thanks.
A bit late, sorry. I expect your data is on the mainframe.
It sounds like you want an ODBC connection to a database. You will need to check with your architects or DBA's for specifics, e.g. does the DBMS product have a "client side" component you can direct this through? Otherwise performance and sociability may be a concern. There are better 3rd party clients, are you committed to VBA?
The name of your application (or the stage of the life cycle is not important).
The size of your data is very important. How many hundred million records?
You could alternatively pull the data all at once. You may be allowed access to a backup.
There are a number of ways data can be pulled from the mainframe. You can format it into csv first, or you may have a language that will build an xls file. Traditionally the MS product was Access back in the days when excel had a restrictive limit on the number of records (50K?), and if you want an ODBC connection
IND$FILE transfer from ISPF Panel 3.6 by means of a TN3270 terminal on your desktop. If your shop is sophisticated, you may have a cli script as well.
sftp transfer, SSH, SCP, Telnet and bear in mind you will need a landing area.
Any managed Queue product, such as MQSeries.
Media, even optical.
You may have a transmission product such as CA-XCOM.
This is bread and butter stuff, even if you have EBCDIC on a Wintel stack you can decode():encode() with Python. I would expect you to be IBM500, but you should confirm this as well.
So yes, colleagues, or even search your source repositories for JCL with these keywords.
So a bit of a general question. I work as a data analyst for a startup. My primary process involves taking existing customer data a client has and cleansing/normalizing it to fit into our platform once as part of our onboarding process. A member of our team exports their data from their system they are transitioning from or, if they kept track of it in house, we receive their Excel log they used to track it. It is always in a different format and requires extensive cleansing (avg 1 min/record). We take what is usually one large table (.xlxs format), and after cleansing, split it into four .csv files; which we load as four tables on our platform.
I feel I have optimized the process quite well in terms of the process steps and cleansing with excel functions (if, concat, text-to-columns, etc). I have beginner-intermediate skills in VBA and SQL and have just scratched the surface in R; what is frustrating is that I know there is the potential to automate this process but I just don't know where to start. If anyone has experience with something like this, code, a link to an article / another thread, or just some general direction would be much appreciated. Please ask for clarification where you feel it is needed. Thanks.
This will be really hard to do in Excel. If you have the time you can try out Optimus, a Data Cleansing library written in Python and Pyspark (you don't need to know spark). Here is the webpage https://hioptimus.com.
You can create Data Pipelines with it, and I recommend that you do that, try to generalize your processes, and asking the client for more a structure way of passing the data.
The good thing is that you don't need Big Data for running Optimus, bit if you have it some day, the same code will work.
Check out the documentation for more:
http://optimus-ironmussa.readthedocs.io/en/latest/
Let me know if you have doubts!
I'm developing an add-in for Excel using the Office Add-ins platform. In this add-in I'm writing data to a range using the setSelectedDataAsync** function. It works fine, but after the data is written, I'm not able to delete or edit the cells (although I can select new ranges) unless I click anywhere outside the worksheet or double click a cell. I think it is an issue with Excel not regaining focus correctly (the filename in the top of the app remains grayed out).
Some users seem to think that Excel becomes unresponsive, which is a problem.
Is this a known issue? Is there a work around for this?
** I have noticed that setSelectedDataAsync is way, way quicker than setting range.values to a matrix and then ctx.sync(). Am I losing some important functionality by not using the latter method?
This is not a known issue (unable to interact with worksheet after setting the data). We can look into that.
Surprised to hear that setSelectedDataAsync works faster than the range.values set. The batched syntax allows you to combine not just one instruction, but many related instructions such as setting number format, font, background, etc. and you can do a single sync() to send all instructions in one batch. So, it is more efficient when you combine related instructions together.
There is no restriction of which API to use as such; however the Excel1.1 version was introduced with Office 2016 and then there have been many releases since then incrementally adding new features along the way.
setSelectedDataAsync() API was designed to work across hosts such as Excel, Word, etc. and hence doesn't go deeper in-terms of setting number format, formats, etc.
Our customers use 500+ applications and we would like to integrate these applications with our. What is the best way to do that? These applications are time registration applications and common for most of them is that they can export to csv or similar, some of them are actually home-brewed excel sheets where time is registered.
The best idea so far is to create our own excel sheet, which can be used to integrate with all these applications. The integrations could be in the form of cells containing something like ='[c:\export.csv]rawdata'!$A$3 Where export.csv is the csv file exported from the time registration applications. Can you see a better way to integrate against all these applications? It should be mentioned that almost all our customers have Microsoft Office.
Edit: Answers to the excellent questions from Pontus Gagge:
How similar are the data in the different applications?
I assume that since they time registration applications, they will have some similarities, but I assume that some will register the how long time one has worked in total for a whole month, while others will spesify for each day. If Excel is chosen, I believe that many of the differences could be ironed out using basic formulas.
What quality is the data?
The quality of the data can vary so basic validation must be undertaken, a good way is also to make it transparent for the customers, how our application understands their input, so they are responsible.
How large amounts of data are you talking about?
There will be information about the time worked for up to 50 employees.
Is the integration one-way only?
Yes
With what frequency should information be transferred?
Once per month (when they need to pay salaries).
How often do the applications themselves change, and how often does your product change?
If their application is a home-brewed Excel sheet, then I assume it will change once a year (due for example a mistake someone). If it is a standard proper time registration application, then I do not believe they are updated more often than every fifth year or so, as it is a very stabile concept.
Should the integration be fully automatic or can your end users trigger a data transfer?
They can surely trigger data transfer. The users are often dedicated to the process so they can be trained at doing it, which means that they could make up to, say 30, mouse clicks in order to integrate each month.
Will the customers have somebody to monitor the integrations?
As we have many customers, many of them should be able to undertake the integration themselves. We will though be able to assist them over the telephone. We cannot, though undertake the integration ourselves because we would then be responsible for any errors due to user mistakes, etc.
Does the phrase 'integration spaghetti' mean anything to you...?
I am looking for ideas from the best chefs to cook a nice large portion of that.
You need to come up with a common data format, and a way to translate the individual data formats to the common format. There's really no way around this - any solution you come up with will have to do this in one way or the other. It's the essential complexity of what you're doing.
The bigger issue is actually variances within the source data, in terms of how things like dates are stored, missing columns, etc. Doing a generic conversion for CSV to move columns around is comparatively easy.
I would also look at CSV and then use an OLEDB connection against the CSV file for importing.
If you try to make something that can interface to any data structure in the universe (and 500 is plenty close enough), it is guaranteed to be a maintenance nightmare. Instead I would approach this from multiple angles:
Devise an interface into which a human can enter this data already in the proper format. With 500+ clients, I'd make this a small, raw but functional browser based site that users can use to enter this information manally. This is the fall-back. At the end of the day, a human can re-key the information into the site and solve the import issue. Ideally, everyone would use this instead of their own format. Data entry people are cheap.
Similar to above, but expanded, I would develop a standard application or standardize on an off-the-shelf application that can be used to replace their existing format. This might take more time than #1. The goal would be to only do one-time imports of these varying data schemas into the application and be done with them for good.
The nice thing about spreadsheets is that you can do anything anywhere. The bad thing about spreadsheets is that you can do anything anywhere. With CSV or a spreadsheet there is simply no way to enforce data integrity and thus consistency (which is the primary goal) on the data. If the source data is already in a database, then that is obviously simpler.
I would be inclined to use database format into which each of these files need to be converted rather than a spreadsheet (e.g. use something like Jet (MDB)). If you have non-Windows users then that will make it harder and you might have to use a spreadsheet. The problem is that it is too easy for the user to change their source structure, break their upload and come crying to you. If a given end user has a resident expert, they can find a way of importing the data into that database format . If you are that expert, then I would on a case-by-case basis, write something that would import into that database format. XML would be the other choice, but that will likely take more coding than an import/export into a database format.
Standardization of the apps (even having all the sources in a database format instead of a spreadsheet would help) and control over the data schema is the ultimate goal rather than permitting a gazillion formats. There really is no nice answer other than standardization. Otherwise, you are having to write a converter for every Tom-Dick-and-Harry format and again when someone changes the source format.
With a multitude of data sources mapping each one correctly to an intermediate format is not trivial. Regular expressions are good with a finite set of known data formats. Multipass can help when data is ambiguous without context (month,day fields and have several days of data), and also help defeat data entry errors. But it seems as this data is connected to salaries there needs a good reliable transfer.
An import configuring trick
Get the customer to make a set of training data in the application. It should have a "predefined unique date" and each subsequent data field have a number corresponding to the target data field in your application. On importing your application needs to recognise the predefined date, determine the unique translation required and effect the displaying/saving of this "mapping key", and stop the import. eg If you expect "Duration hours" in field two then get the user to enter 2 in the relevant field which might be "Attendance hours".
On subsequent runs, and with the mapping definition key, import becomes a fairly easy process of translation.
Note on terms
"predefined date" - must be historical, say founding date of your company?, might need to be in PC clock settable range.
"mapping key" - could be string of hex digits and nybble based so tractable to workout
The entered code can be extended to signify required conversions ie customer's application has durations in days and your application expects it in hours.
Interfacing with windows programs (in order if increasing fragility)
Ye Olde saving as CSV file
Print to operating system printer that is setup as a text file/pdf, then scavenge the data out of that
Extract data via the application interface control, typically ActiveX for several windows programs ie like Matlab's Spreadsheet Link
Read native file format xls format ie like Matlab's xlsread
Add an additional intermediate spreadsheet sheet that has extended cell references ie ='[filename]rawdata'!$A$3
Have a look at Teiid by JBoss: http://jboss.org/teiid
Also consider using SOA - e.g., if you're on Java, try JBoss SOA platform: http://www.jboss.com/resources/soa/?intcmp=1004
Use a simple XML format. A non-technical person can easily understand a simple XML format (and could even identify basic problems with XML documents that are not well-formed).
Maybe use a DTD (or even better an XML schema) to do very basic validation, and then supplement this with an XSL stylesheet to do more validation with better error reporting. (An XSL stylesheet simply converts from XML to something else and so can be generate readable error messages.)
The advantage of this approach is that web browsers such as Internet Explorer can apply the XSL stylesheets. A customer need only spend at most a day enhancing their applications or writing excel macros to generate the XML data in the format that you specify.
Recent versions of Excel have support for converting spreadsheet data to XML, and can even validate against schemas.
Once the data passes the XSL validation checks, you have validated XML data.
If you have heaps of data and heaps of money, you could look at existing data management and cleansing tools:
http://www-01.ibm.com/software/data/infosphere/datastage
http://www-01.ibm.com/software/data/infosphere/qualitystage
But even then, you'll likely need to follow kyoryu's suggestion assuming you have 500+ data formats. The problem isn't your side. You need them to standardize their output formats if you have no control over their apps. CSV is likely the easiest. You could even send them a excel template to help them along.