So I have a process, which VP and SVP doing the same task evaluation like collaboration
But I know that 1 Lane only for 1 Actor, so how to draw it in BPMN?
A lane does not have to represent a single role / person. It can also represent organizational units (group of users,...).
Either use an abstract description of the group performing the tasks together or use two lanes if you want to model more detail.
Related
We would like to ask a question, we have several lanes (Y categories), mainly we create many lanes per category, in my example below, the cat LXXXXXX has 2 lanes, one with milestones the other lane with a pill, our question is, can web setup the following type of structure in a hierarchical way? in other words Thank you for all your help.
I'm working on a quarterly report. The report should look something like this:
col
Calculation
Source table
Start_Balance
Sum at start of time period
Account_balance
Sell Transactions
Sum of all sell values between the two time periods
Transactions
Buy Transactions
Sum of all buy values between the two time periods
Transactions
End Balance
Sum at the end of time period
Account_balance
so e.g.
Calculation
sum
Start_Balance
1000
Sell Transactions
500
Buy Transactions
750
End Balance
1250
The problem here is that I'm working with a relational star schema, one of the facts is semi-additive and the other is additive, so they behave differently on the time dimension.
In my case I'm using Cognos analytics, but I think this problem goes for any BI tool. What would be best practice to deal with this issue? I'm certain I can come up with some sql query that combines these two tables into one table which the report reads from, but this doesn't seem like best practice, or is it? Another approach would be to create some measures in the BI tool, I'm not a big fan of this approach because it seems to be least sustainable approach, and I'm unfamiliar with it.
For Cognos you can stitch the tables
The technique has to do with how Cognos aggregates
Framework manager joins are typically 1 to n for describing the relationship
A star schema having the fact table in the middle and representing the N
with all of the outer tables describing/grouping the data, representing the 1
Fact tables, quantitative data, the stuff you want to sum should be on the many side of the relationship
Descriptive tables, qualitative data, the stuff you want to describe or group by should be on the 1 (instead of the many)
To stitch we have multiple tables we want to be facts
Take the common tables that you would use for grouping, like the period (there are probably some others like company, or customer, etc)
Connect each of the fact tables with the common table (aka dimension) like this:
Account_balance N to 1 Company
Account_balance N to 1 Period
Account_balance N to 1 Customer
Transactions N to 1 Company
Transactions N to 1 Period
Transactions N to 1 Customer
This will cause Cognos to perform a full outer join with a coalesce
Allowing you to handle the fact tables even though they have different levels of granularity
Remember with an outer join you may have to handle nulls and you may need to use the summary filter depending on your reporting needs
You want to include the common tables on your report which might conflict with how you want the report to look
An easy work around is to add them to the layout and then set the property to box type none so the sql behaves you want and the report looks the way you want
You'll probably need to setup determinants in the Framework Manager model. The following does a good job in explaining this:
https://www.ibm.com/docs/en/cognos-analytics/11.0.0?topic=concepts-multiple-fact-multiple-grain-queries
Multiple employees work together to complete a task. If the first employee can complete 70% of the task in his working time, the remaining 30% needs to be assigned to the second employee. How to use streamapi to define constraint rules and calculate the start time and end time of its task.
Would it be possible to have two separate tasks instead, where the second one depends on the first one (and thus, it cannot start before the first task completes)?
The dependency between the two tasks can be implemented as a hard constraint.
The first question is how to design the models you use for this. I assume you have a Set<Task> tasks that has a total required time to be completed by Set<Employee> employees? Then you may create List<TaskAssignment> that can aggregate a Set of employees to complete the task were each assigned employee can contribute by different parts. Depending on the complexity of how and when employees can work on a task can make it more challenging though but should be straightforward.
This is more a general question about graph database design, and I couldn't find a better title for my question.
I have Producer A and Producer B, who both produce apples. I buy these apples from them, but from A only 10,000 and from B 20,000.
How to draw this in a graph database, if I would like to have the amount of apples that I buy as a node (not as a relation attribute)?
As far as I can imagine it, I'd have two nodes of type "Producer", one node of type "Good", and two nodes of type "Buying Amount". Additionally there are two types of relations: "produces" and "needs_to_be_produced". (I am not sure if the relation titles are fiiting).
Here is a drawing: http://img198.imageshack.us/img198/3964/4klk.png
The problem here is: Where do I know from if Producer A or B needs to produce 10,000 apples for me?
I am open for any proposals and changes, but I would like to keep the amount of produced apples as a node.
Thanks!
Below is how I've modeled. I've setup the test data and sample query for you here.
What quantity of a particular goods have been purchased from various producers
MATCH t:Transaction-[:FOR]->g:Goods, t-[:FROM]->producer WHERE g.type='Apples' RETURN producer, t.quantity, t.month+"-"+t.year AS Date
Output
Design
Nodes: Goods (type), Transaction (quantity, date(month, year)), Producer (name)
Relationships: A Transaction is FOR a particular Goods and indicates that the purchase was FROM a particular Producer
Setup
CREATE (producerA:Producer {name:'A'})
CREATE (producerB:Producer {name:'B'})
CREATE (apples:Goods {type:'Apples'})
CREATE producerA-[:PRODUCES]->apples
CREATE producerB-[:PRODUCES]->apples
CREATE (trans1:Transaction {month:'08', year:'2014', quantity:'10000'})-[:FOR]->apples
CREATE trans1-[:FROM]->producerA
CREATE (trans2:Transaction {month:'08', year:'2014', quantity:'20000'})-[:FOR]->apples
CREATE trans2-[:FROM]->producerB
I would introduce another node type, let's call it "purchase" (although I'm not sure what the best name is, would need more details about your use case).
(Producer A)-[:PRODUCES]->(Purchase X)
(Producer B)-[:PRODUCES]->(Purchase Y)
(Purchase X)-[:IS_FOR_PRODUCT]->(Apple)
(Purchase Y)-[:IS_FOR_PRODUCT]->(Apple)
(Purchase X)-[:IS_FOR_AMOUNT]->(10,000)
(Purchase Y)-[:IS_FOR_AMOUNT]->(20,000)
I hope the syntax is clear, () are nodes and -[:]-> are named directed relationships, like in Cypher.
I have carried out an evaluation of a product using likert scale questionnaire and imported the date into SPSS. I have my columns arranged as follows:
ID, Group, Q1, Q2, Q3, Q4
I have two different groups completing the questionnaire, with each person a different numerical ID. Under the Q columns, I have the score given for that person (from 1-5) from the Likert Scale.
In all there are over 300 responses.
I am running analysis using 'descriptive statistics/frequencies' from the menubar and not getting the tables I am looking for. Basically, it is including all respondents together, whereas I would like it to compare the two groups in the tables.
How can I get descriptive statistics on questionnaire items by group using SPSS?
In addition, if you have any further tips as to what analysis I could perform on this type of data in SPSS I'd be most grateful. I'd like to show that there isn't a significant difference in opinions between the groups, and from looking at the data, it appears that this is the case.
One option
split file by group
run descriptive statistics as usual
See this SPSS FAQ item from UCLA on how to analyze data by categories.
The short answer to you question is, crosstabs Q1 to Q4 by group. will produce the table you want. Or if you have the ctables package available a more compact table will be produced by
variable level group_id Q1 to Q4 (nominal).
ctables
/table Q1 + Q2 + Q3 + Q4 by group_id.
Either can be elaborated on to produce other statistics if wanted. It seems to me a chi-square test would be sufficient for your question.
As far as further analysis it is a bit of an open-ended question that needs more focus to be able to effectively answer. I frequently suggest visual exploration for such exploratory analysis, and hence I would suggest perusing this question on the site, Visualizing Likert responses using R or SPSS for potential ideas about how to visualize the responses. Another motivating post may be How to visualize 3D contingency matrix?.
There are a ton of other questions related to analyzing likert responses on this site though, and it is difficult to give any more specific advice without a more specific motivation for the analysis.
While the above answers all have their good points, I usually prefer this procedure (type the following into a syntax window and Run):
means q1 to q4 by group/stat anova.
This will give you group means, sample sizes, and standard deviations as well as tests of the difference in means between the groups, for each of the variables Q1 to Q4. Of course, the tests will only give you valid results to the extent that your data meet the standard assumptions of anova. Some may say that variables measured on an ordinal 1-5 scale are not suitable for anova, and in academic contexts this is often true, but in business contexts most people are willing to sacrifice some rigor for the sake of convenience. It's much more convenient to compare 4x2=8 means than it is to compare the distributions of 4x5x2=40 categories of responses.
This can easily be done by using the "Crosstabs" function in SPSS for Windows:
Analyze --> Descriptive Statistics --> Crosstabs. Move the dependent variable(s) into the "Row(s)" box, then move the grouping variable into the "Column(s)" box, then click OK.