I tried to get the step count by date wise. When I took the data from google fit using
API:
https://www.googleapis.com/fitness/v1/users/me/dataSources/derived:com.google.step_count.delta:com.google.android.gms:estimated_steps/datasets/1457548200000000000-1457631000000000000&token=1111111111
I can get only limited step count but not all the steps on that date. Why this kind of problem's are occurs to get the google fit data.
Can any one suggest me the better way to get all the data from google fit.
Using derived:com.google.step_count.delta:com.google.android.gms:estimated_steps datasource
will give you varying results depending on the scenario. The cause of this is mainly from the sensors used. Maybe this is the reason why you think that you have limited results.
estimated_steps also takes into account activity, and estimates steps
when there are none. For instance, assume the user walked for 30
minutes, but the hardware step counter only recorded 10 steps. We
know that number is inaccurate so instead we estimate, say 3000 steps
during that time.
This was noted and discussed in this SO post.
We are bumping into limitations with Flurry. We use events and parameters to track some game play info (like number of KO/map) but 1/ the limit of 15 parameters per event is a problem and 2/ the visualisation is not good (for instance Ko/map is shown by map so we have to open each event one after another).
We are trying to build a better visualisation with excel using the CSV files provided by Flurry, but then again we need to download the 50+ CSV files and it's really not convenient.
Is there a way to get all the information in one CSV or to get the information another way?
As a side note Flurry support is not answering any of our emails. :(
thanks for your help!
Have you tried checking out playtomic instead. Sounds like it might match your problem better.
They have an API to access your data. So you should be able to access it realtime.
You might also want to check out www.parse.com
We (my company) runs a website which have lots of data recorded like user registration, visits, clicks, what the stuff they post etc etc but so far we don't have a tool to find out how to monitor entire thing or how to find patterns in it so that we can understand what kind of information we can get from it? So that Mgmt can take decisions based on it. In short, the people do at Amazon or Google based on data they retrieve, we want a similar thing.
Now, after the intro, I would like to know what technology could it be called;is it Data Mining,Machine Learning or what? Where should we start to convert meaningless data into useful Information?
I think what you need enters in the "realm" of: parsing data, creating graphs, showing statistics about some elements, etc.
There is no "easy" answer, I can only answer parts of your question.
There are no premade magical analytical tools, big companies have their own backend tools tunned to parse the large amounts of data and spit out data summaries that are then used to build graphs or for statistical analysis.
I think the domain you are searching for is statistical data analysis. But there are many parts that go together here.
Best advice I can give you is to set up specific goals for you analysis and then try to see what is the best solution, you question is too open.
ie. if you are interested in visits/clicks/website related statistics Google Analytics is a great tool, and very easy to use.
I've just gotten into the Adwords API for an upcoming project and I need something quite simple actually, but I want to go about it the most efficient way.
I need code to retrieve the Global Monthly Search Volume for multiple keywords (in the millions). After reading about BulkMutateJobService, in the Google documentation they say
If you want to perform a very large number of operations (up to 500,000) on your AdWords campaigns and child objects, use BulkMutateJobService
But later on in the page they give limits of
No more than 25 OperationStream objects are allowed.
No more than 10,000 operations are allowed per BulkMutateRequest.
No more than 100 request parts are allowed.
as well as a few others. See source here http://code.google.com/apis/adwords/docs/bulkjobs.html
Now, my questions:
What do these numbers mean? If I have 1 million words I need information on, do I only need to perform 2 requests with 500K words each?
Also, are there examples of code that does this task?
I only need Global Monthly Search Volume and CPC for each keyword. I've searched online, but to no avail have I found any good example or anything leaning in that direction that utilizes BulkMutateJobService.
Any links, resources, code, advice you can offer? All is appreciated.
The BulkMutateJobService only allows for mutates, or changes, to the account. It does not provide the bulk retrieval of information.
You can fetch monthly search volume for keywords using the TargetingIdeaService. If you use it in STATS mode you can include up to 2500 keywords per request.
Estimates CPC values are obtained from the TrafficEstimatorService. You can request up to 500 keywords per request.
FYI, there is an official AdWords API Forum that you can ask questions on.
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.