I am new to Qlikview and after several failed attempts I have to ask for some guidance regarding charts in Qlikview. I want to create Line chart which will have:
One dimension – time period of one month broke down by days in it
One expression – Number of created tasks per day
Second expression – Number of closed tasks per day
Third expression – Number of open tasks per day
This is very basic example and I couldn’t find solution for this, and to be honest I think I don’t understand how I should setup my time period dimension and expression. Each time when I try to introduce more then one expression things go south. Maybe its because I have multiple dates or my dimension is wrong.
Here is my simple data:
http://pastebin.com/Lv0CFQPm
I have been reading about helper tables like Master Callendar or “Date Island” but I couldn’t grasp it. I have tried to follow guide from here: https://community.qlik.com/docs/DOC-8642 but that only worked for one date (for me at least).
How should I setup dimension and expression on my chart, so I can count the ID field if Created Date matches one from dimension and Status is appropriate?
I have personal edition so I am unable to open qwv files from other authors.
Thank you in advance, kind regards!
My solution to this would be to change from a single line per Call with associated dates to a concatenated list of Call Events with a single date each. i.e. each Call will have a creation event and a resolution event. This is how I achieve that. (I turned your data into a spreadsheet but the concept is the same for any data source.)
Calls:
LOAD Type,
Id,
Priority,
'New' as Status,
date(floor(Created)) as [Date],
time(Created) as [Time]
FROM
[Calls.xlsx]
(ooxml, embedded labels, table is Sheet1) where Created>0;
LOAD Type,
Id,
Priority,
Status,
date(floor(Resolved)) as [Date],
time(Resolved) as [Time]
FROM
[Calls.xlsx]
(ooxml, embedded labels, table is Sheet1) where Resolved>0;
Key concepts here are allowing QlikView's auto-conatenate to do it's job by making the field-names of both load statements exactly the same, including capitalisation. The second is splitting the timestamp into a Date and a time. This allows you to have a dimension of Date only and group the events for the day. (In big data sets the resource saving is also significant.) The third is creating the dummy 'New' status for each event on the day of it's creation date.
With just this data and these expressions
Created = count(if(Status='New',Id))
Resolved = count(if(Status='Resolved',Id))
and then
Created-Resolved
all with full accumulation ticked for Open (to give you a running total rather than a daily total which might go negative and look odd) you could draw this graph.
For extra completeness you could add this to the code section to fill up your dates and create the Master Calendar you spoke of. There are many other ways of achieving this
MINMAX:
load floor(num(min([Date]))) as MINTRANS,
floor(num(max([Date]))) as MAXTRANS
Resident Calls;
let zDateMin=FieldValue('MINTRANS',1);
let zDateMax=FieldValue('MAXTRANS',1);
//complete calendar
Dates:
LOAD
Date($(zDateMin) + IterNo() - 1, '$(DateFormat)') as [Date]
AUTOGENERATE 1
WHILE $(zDateMin)+IterNo()-1<= $(zDateMax);
Then you could draw this chart. Don't forget to turn Suppress Zero Values on the Presentation tab off.
But my suggestion would be to use a combo rather than line chart so that the calls per day are shown as discrete buckets (Bars) but the running total of Open calls is a line
Related
EDITED (AGAIN): added tables and two screenshots (one of Google Sheets Chart and another showing mutliple issues in DS) to help demonstrate what I am seeing.
Short Version: I have created a parameter to help me score trending topics based on the date range filter. However, I want to be able to show a range of dates' worth of data, not just a specific date's worth of data. In theory, I could make the parameter a checklist with a huge range, but that doesn't seem efficient or sustainable down the road.
Disclaimer: I am about a week into SQL and Data Studio.
Long Version: We are tracking trends over time from a specific customer data set. I'd like to make it so that when a user adjusts the time range, various topics’ " score " depends on the end date. For instance, every time the topic "Recession" is brought up, it is given a score. That score is weighted based on when it was said. I was using 365 as the highest possible score so that anything over a year is null. So if "Recession" is referenced twice, once a week ago and once today, the avg score for recession is 361.5, but if a reference is made to the topic "Talent Management" twice today, then it would have a score of 365, and so forth across a growing list of 50+ topics pertaining to 50+ specific communities we are tracking the topics across.
Here is an example:
topics
groups
entry_date
recession
A
2022-11-24
talent mgt
A
2022-11-24
recession
B
2022-11-22
economy
A
2022-11-22
recession
C
2022-11-15
talent mgt
B
2022-11-8
This score would then affect the bubble size on a chart where the Y-axis is the count of unique groups referencing the topics, and an x-axis based on the range of average scores.
The goal is to be able to see which topics are the most common across groups, which ones are emerging trends, and which ones are dated trends by having a range slider. That way users (colleagues in other departments) can play with the date range "see" the bubbles moving in location and size.
example of static chart in google sheets
I could then also use the same data and fields to measure the percentage of topics being discussed across groups based on the weighted averages against a time range.
In Goolge Sheets I can do this with an xLookUp to a tab that has a column of 0-365 and then next to it a column of 365-0 (on a tab called 'scales') and then a cell on a sheet that you can put any date as the point in time, and it affects all the scores, tables, charts, etc. (I used. =xlookup((point_in_time - entry_date), 'scales'!A:A, 'scales'!B:B, "0")
In the data studios custom SQL I used:
SELECT
*
FROM
`qRaw_data'
where
DATE(_entry_dates_) between
parse_date('%Y%m%d', #DS_START_DATE) and
parse_date('%Y%m%d', #DS_END_DATE)
AND
#pit_date_diff = date_diff(
parse_date('%Y%m%d', #ds_end_date),
_entry_dates_,
day
)
Then I created a field that is time_score of:
avg((Pit_Date_Diff-365)*(-1))
I have been googling and youtubing like crazy and think I either have to come up with a way to override the #pit_date_diff default value OR I need to use a CASE WHEN in the custom query where each time the date_diff is 1 then 365, and so on, but when I try that I get all sorts of errors.
I would like below to include all topics averaged based on all entry dates, not just those that correlate with the inputted parameter field.
currently, I can only show specific entry dates due to the parameter
I appreciate any and all help. I am a week into using data studio and am going cross-eyed Googling and YouTubing things. There is likely a better logical path to accomplish all this. Hoping for a holiday miracle.
Thanks in advance.
It turns out this was much easier than I realized... I added an AS syntax to create a column and then created a field that created the same metrics that I had in the Google Sheets:
SELECT
*,
(date_diff(parse_date('%Y%m%d', #ds_end_date), _entry_dates_,day)) AS q_time_diff
FROM
`qRaw_data`
Then the score field is: (avg(q_time_diff)-365)*(-1)
In case that helps any others in the future... ¯\(ツ)/¯
Happy Holidays!
I have an application which calls the database multiple times to achieve one simple goal.
A little information about this application; In short, the application scrapes data from a webpage & stores specific information from this page into a database. The important information in this query is: Player name, Position. There can be multiple sitting at one specific position, kill points & Class
Player name has every potential to change or remain the same every day
Regarding the Position, there can be multiple sitting in one position
Kill points has the potential to increase or remain the same every day
Class, there is only 2 possibilities that a name can be, Ex: A can change to B or remain A (same in reverse), but cannot be C,D,E,F
The player name can change at any particular day, Position can also change dependent on the kill point increase from the last update which spins back around to the goal. This is to search the database day by day, from the current date to as far back as 2021-02-22 starting at the most recent entry for a player name and back track to the previous day to check if that player name is still the same or has changed.
What is being used as a main reference to the change is the kill points. As the days go on, this number will either be the exact same or increase, it can never decrease.
So now onto the implementation of this application.
The first query which runs finds the most recent entry for the player name
SELECT TOP(1) * FROM [changes] WHERE [CharacterName]=#charname AND [Territory]=#territory AND [Archived]=0 ORDER BY [Recorded] DESC
Then continue to check the previous days entries with the following query:
SELECT TOP(1) * FROM [changes] WHERE [Territory]=#territory AND [CharacterName]=#charname AND [Recorded]=#searchdate AND ([Class] LIKE '%{Class}%' OR [Class] LIKE '%{GetOpposite(Class)}%' AND [Archived]=0 )
If no results are found, will then proceed to find an alternative name with the following query:
SELECT TOP(5) * FROM [changes] WHERE [Kills] <= #kills AND [Recorded]='{Data.Recorded.AddDays(-1):yyyy-MM-dd}' AND [Territory]=#territory AND [Mode]=#mode AND ([Class] LIKE #original OR [Class] LIKE #opposite) AND [Archived]=0 ORDER BY [Kills] DESC
The aim of the query above is to get the top 5 entries that are the closest possible matches & Then cross references with the day ahead
SELECT COUNT(*) FROM [changes] WHERE [CharacterName]=#CharacterName AND [Territory]=#Territory AND [Recorded]=#SearchedDate AND [Archived]=0
So with checking the day ahead, if the character name is not found in the day ahead, then this is considered to be the old player name for this specific character, else after searching all 5 of the results and they are all found to be present in the day aheads searches, then this name is considered to be new to the table.
Now with the date this application started to run up to today's date which is over 400 individual queries on the database to achieve one goal.
It is also worth a noting that this table grows by 14,400 - 14,500 Rows each and every day.
The overall question to this specific? Is it possible to bring all these queries into less calls onto the database, reduce queries & improve performance?
What you can do to improve performance will be based on what parts of the application stack you can manipulate. Things to try:
Store Less Data - Database content retrieval speed is largely based on how well the database is ordered/normalized and just how much data needs to be searched for each query. Managing a cache of prior scraped pages and only storing data when there's been a change between the current scrape and the last one would guarantee less redundant requests to the db.
Separate specific classes of data - Separating data into dedicated tables would allow you to query a specific table for a specific character, etc... effectively removing one where clause.
Reduce time between queries - Less incoming concurrent requests means less resource contention and faster response times to prior requests.
Use another data structure - The only reason you're using top() is because you need data ordered in some specific way (most-recent, etc...). If you just used a code data structure that keeps the data ordered and still easily-query-able you could then perhaps offload some sql requests to this structure instead of the db.
The suggestions above are not exhaustive, but what you do to improve performance is largely a function of what in the application stack you have the ability to modify.
I have a fact table of Delay by Date by Category (and many other Fields). I have another (target) table of DelayTarget by Month and Category.
I am currently associating the target table to the fact table on Month & Category but when there is no Delay for a given Category in a given Month, then the DelayTarget value does not display in my dashboard.
How do I associate the DelayTarget to all Months in my main dataset - even when there is no Delay to report? I think I want to create a Zero value for Delay when it is null but I don't know how to do this or if this is the best method.
You need to create MasterCalendar to fill gap in dates.
I can give you more detailed answer but the best would be to share you data model (ctrl +T) and some example data from tables (or even better just.qvw)
I am currently trying to implement the following scenario on Tabular Mode SSAS, appreciate your support.
We have a fact table of Transactions that is the linked to the customer dimension, and we have a measure called Frequency that shows the number of times the user used his card during the selected period (The fact table is also linked to Date Dimension). What we need to do is create a dimension that would have the frequency groups as follows (For example, 1 to 5, 5 to 10 , 10 to 15 and 15 & Above). The problem here is that I am unable to link the Fact table to this dimension becuase the link between them would be a calculated measure.
Any thoughts?
Thanks and Best Regards
Omar Sultan
If you want to link the fact to a bucket dimension, you are going to have to specify the time granularity. I would suggest that you decide one or more useful periods (day, week, month) and create a facts (or several) to bucket your data at the appropriate grain.
This solution will lose flexibility from your original request, as the user will not be able to dynamically select the time period for the bucket, however they will gain from being able to compare fixed time periods to identify trends over time.
I need to scheduled events, tasks, appointments, etc. in my DB. Some of them will be one time appointments, and some will be reoccurring "To-Dos" which must be checked off. After looking a google's calendar layout and others, plus doing a lot of reading here is what I have so far.
Calendar table (Could be called schedule table I guess): Basic_Event Title, start/end, reoccurs info.
Calendar occurrence table: ties to schedule table, occurrence specific text, next occurrence date / time????
Looked here at how SQL Server does its jobs: http://technet.microsoft.com/en-us/library/ms178644.aspx
but this is slightly different.
Why two tables: I need to track status of each instance of the reoccurring task. Otherwise this would be much simpler...
so... on to the questions:
1) Does this seem like the proper way to go about it? Is there a better way to handle the multiple occurrence issue?
2) How often / how should I trigger creation of the occurrences? I really don't want to create a bunch of occurrences... BUT... What if the user wants to view next year's calendar...
Makes sense to have your schedule definition for a task in one table and then a separate table to record each instance of that separately - that's the approach I've taken in the past.
And with regards to creating the occurrences, there's probably no need to create them all up front. Especially when you consider tasks that repeat indefinitely! Again, the approach I've used in the past is to only create the next occurrence. When that instance is actioned, the next instance is then calculated and created.
This leaves the issue of viewing future occurrences. For this, you can start of with the initial/next scheduled occurrence and just calculate the future occurrences on-the-fly at display time.
While this isn't an exact answer to your question I've solved this problem before in SQL Server (though database here is irrelevant) by modeling a solution based on Unix's cron.
Instead of string parsing we used integer columns in a table to store the various time units.
We had events which could be scheduled; they could either point to a one-time schedule table that represented a distinct point in time (a date/time) or to the recurring schedule table which is modelled after cron.
Additionally remember to model your solution correctly. An event has a duration but the duration is unrelated to the schedule (but an event's duration may impact the schedule by causing conflicts). Do not try to model duration as part of your schedule.
In the past when we've done this, we had 2 tables:
1) Schedules -> Includes recurrence information
2) Exceptions -> Edit/changes to specific instances
Using SQL, it's possible to get the list of "Schedules" that have at least one instance in a given date range. Then you can expand in the GUI where each instance lies.