I need to know the difference between BAPI_ACC_GL_POSTING_POST and BAPI_ACC_DOCUMENT_POST that are very similar.
BAPI_ACC_GL_POSTING_POST seems to be a simpler, functionally estricted BAPI for posting documents in general ledger. BAPI_ACC_DOCUMENT_POST is more general, can post documents in general ledger as well as in other areas like billing, goods movement etc.
BAPI_ACC_GL_POSTING_POST seems to exist to make posting documents in general ledger a bit easier.
Related
I have a business team asking me about setting up a meeting to explain them about database design considerations. Since they do not have much idea on RDMS I'm to thinking to explain below things
What is RDBMS
What is a table and what are constraints / why we need them
What is a transaction and what are ACID Properties
Things to consider before/while developing a dbms
a. Decide how much detail you need and how much you may in need future
b. Identify fields with unique values
c. Select the appropriate data types for your fields
d. Normalization and Index design
Also most of the time this team has their data coming in from flat files which we need to load into the DB and represent into the format they need. Anybody please suggest what can i explain more or any better way I can explain. And kind of their data is all over the place. I just want to emphazise more on thinking it through because we couldn't set up a stable process to do the import. Any suggestion for me is welcome as well :)
Appreciate your help!
You haven't said what your audience expects to take away from your presentation. So I'll have to guess, based on my dealings with business people in the past. Your mileage may vary.
Business people typically don't care about the skills and knowledge you put into doing a good job with database design, even when they say they do. They want to understand database design in terms of costs and benefits. That is how business people think.
So if you must cover some technical topic like indexing, do so from a cost benefit point of view. There is a cost to adding an index to a table, and there is a benefit to adding an index to a table. Figuring out in advance whether the benefit is worth the cost is the really tricky part, and they will be interested in this.
On a larger scale, data is a business asset. There is a cost to managing that asset well, and there is a benefit to managing that asset well. If you can connect your talk to these two concepts, they will be interested.
If they are really good business people, they will have a good understanding of the subject matter that the database covers, provided it's a part of the enterprise data that affects their business. If you have a good ER model of the data in the database, this model will connect every value in every table to an attribute, and every attribute will describe some aspect of the subject matter. This is a very different use of an ER model than just using it as a preliminary to creating a relational model.
Technical people tend to think of ER modeling as "relational modeling light". It's really much deeper than that. It's an analytical handle on the question "what does the data really mean?" And this is a handle on "what is the data really worth?". And this is where the technical world meets the business world.
How about starting from the basis of CRUD operations, then move on to normalization, give the scenarios for the need of Normalization and concept of Keys in RDBMS ,then you can talk about the ER modeling
Considering the fact that you are presenting to business folks, I think there would be 2 approaches best suited to your needs.
a) WHEN YOU HAVE LESS TIME:
Only cover topics which need minimum or no prior knowledge. Cover RDMS & things to consider.
Keep it simple and easy to understand. Tell them how your solution works and why it is an effective one.
Cover only topics which are relevant and make it layman friendly. Provide them the pros & cons of your DB design. Connect it to business needs.
In all cases, provide contextual examples which they may relate to with ease.
b) WHEN YOU HAVE MORE TIME
You may cover topics in detail as suggested in the previous comments. (#SQL_Underworld & #Ramya)
which form is a correct OO design?
"Matter of taste" is a mediocre's easy way out.
Any good reads on the subject?
I want a conclusive prove one way or the other.
EDIT: I know which answer is correct (wink!). What I really want is to see any arguments in support of the former form (order.fill(warehouse)).
There is no conclusive proof and to a certain extent it is a matter of taste. OO is not science - it is art. It also depends on the domain, overall software structure, etc. and so your small example cannot be extrapolated to any OO problem.
However, here is my take based on your information:
Warehouses store things. They don't fill orders. Orders request things. They don't know which warehouse (or warehouses) the things come from. So a dependency in either direction between the two does not feel right.
In the real world, and the software, something would be a mediator between the two. #themel indicated the same in the comment to your question, though I prefer something less programming pattern sounding. Perhaps something like:
ShippingPlan plan = shippingPlanner.fill(order).from(warehouses).ship();
However, it is a matter of taste :-)
In its simplest form warehouse is an inventory storage place.
But it also would be correct to view a warehouse as a facility comprised of storage space, personal, shipping docks etc. If you assume that view of a warehouse then it would be appropriate to say that a warehouse (as a facility) can be charged with filling out orders, or in expanded form:
a warehouse facility is capable of assembling a shipment according to a given specification (an order)
above is a justification (if not proof) for: warehouse.fill(order); form. Notice that this form substantially equivalent to SingleShot's and themel's suggestions. The trick is to consolidate shippingPlanner (an order fulfillment authority) and a warehouse (a inventory storage space). Simply put in my example warehouse is a composition of an order fulfillment authority and an inventory storage space and in SingleShot's those two are presented separately. It means that if such consolidation is (or becomes) unacceptable (for example due to complexity of the parts), then the warehouse can be decomposed into these two sub components.
I can not come up with a justification for assigning fill operation to an order object.
hello? warehouse? yes, please take this order and fill it. thank you. -- that I can understand.
hey, order! the warehouse is over there. do your thing and get fulfill yourself. -- makes no sense to me.
This is something that has always bothered me. Wouldnt it make more sense to have the FROM clause come before the SELECT? Whenever Im writing sql, especially with joins, I always figure out the FROM clause first and then write the SELECT.
Plus, putting the FROM first would allow for better intellisense inside the editor.
Does anyone know what the reasoning was to have SELECT come first? Am I only one who is bothered by this?
Yes it is strange and counterintuitive. Hugh Darwen theorises about how this state of affairs came about:
Do you take SELECT-FROM-WHERE for
granted, or do you, like me, find it
rather curious that the System R team
should have spurned the normal way of
writing expressions of arbitrary
complexity in favour of something
utterly idiosyncratic and, one might
say, rather dictatorial...?
The fact is that in the 1960s various
scripting languages (as we tend to
call such things these days) had come
about for the purposes of report
generation, especially ad hoc report
generation. We had one such language
in the prerelational DBMS called
Terminal Business System (TBS) that I
worked on for IBM from 1969-77. Our
language required the user to specify
the required report in a series of
steps that had to be given in the
prescribed order...
A somewhat similar but much more
sophisticated report generator was
later developed by IBM in the US, as
part of a product called (prosaically,
as was IBM's style in those days)
Generalized Information System
(GIS)... when I first looked at SQL,
my immediate reaction was "Oh no!
Son of GIS? Please not that!" I
might have been quite wrong about
this. The similarity I perceived
might have been illusory and even if
it was not, I have no firm evidence
that anybody in the System R team was
familiar with GIS. The fact remains
that the general style of a fixed
order of actions was the order of the
day at the time. I postulate that
SQL's SELECT-FROM-WHERE arose out of
this fashion.
From HAVING a Blunderful Time
The syntax was to resemble English.
I am trying to understand AdventureWorks Database as most of the good examples on web and books are usually explained taking it as a sample database.
I found few links like
http://msdn.microsoft.com/en-us/library/ms124825(v=sql.100).aspx
http://merc.tv/img/fig/AdventureWorks2008_Conceptual.pdf
http://merc.tv/img/fig/AdventureWorks2008.gif
But I found them insufficient for explaining the business completely.
I tried to practice some queries as well so that I could get more knowledge about its business. But looking at 70 tables, I finds myself no were in the understanding of its Business.
Can you help me giving some good likes where I can get more details about it.
EDIT
I never read northwind database. Is it important to understand it to get a good grasp on AdventureWorks2008
Looking into what you are doing, I think it is not important for you to fully understand the AW business. If would be a better use of your time to understand the queries that are required and just the 2-3 tables in question rather than the entire database.
Even thought the MSTS certification book pulls from the AW DB, understanding that database is not part of the certification. If you have trouble with specific questions from your book, I would suggest you post what you are doing and what result you are trying to achieve.
I can go on explaining the business of AW but it will consume a lot of time as I cannot completely give the business understanding. You will only understand those things that I will describe here. I am currently going through this book- The Microsoft Datawarehouse Toolkit by Ralph Kimball. This is the best book that will give you a detailed understanding of AW business.
The business requirements ranges from a variety of people. From sales to technical people and others. So I suggest you read the first 3 chapters of this book as it simplifies learning the business.
If reading is not feasible I will show you another approach:
AdventureWorks (AW) is an imaginary manufacturer and seller of bicycles and its accessories (Table Production.ProductCategory).
The schemas help a lot in understanding their business, sales, employee data and product info.
The schemas involved in AW database are: HumanResources, Person, Production, Purchasing, Sales.
The table names are self-explanatory to a great extent. A simple query against each table will give you a fair amount of information about data.
You can go through this link that gives a brief overview of schemas used in AW
https://technet.microsoft.com/en-us/library/ms124894(v=sql.100).aspx
Think of yourself an interviewer and then frame questions that you will be asking the officers/managers of AW. Trust me there are lot of pitfalls if you are a newbie. Like, if you ask the question to business: "What do you want in your datawarehouse?" WRONG. This is your job to figure out.
All the best with exploration.
I have found this link below which if you follow the link depending on which sample database you are interested, it explains what it is all about:
https://msdn.microsoft.com/en-us/library/ms124501(v=sql.100).aspx
I have also fouund this ETL (but could not find for other databases):
http://msftdbprodsamples.codeplex.com/wikipage?title=%20AdventureWorksLTDiagram&referringTitle=AWSchemaDiag
I have also found these exercises:
http://sqlzoo.net/wiki/AdventureWorks
I've been looking at the freebase project for storing data. It seems to be a great place to store concrete, objective data like names, locations and dates. Is it a good place to store subjective data like opinions or ratings? Is there another/better open data, semantic data store or strategy for storing and querying this kind of information?
Additionally, since it is subjective I can be sure that others will not agree with my opinion. How would I store the opinions of others inline so the crowd opinion could be represented better?
Is freebase the right place to store this type of data?
For example: a restaurant rating or a movie rating. The movie rating would probably be less time sensitive than the restaurant rating. Any non-identifying information about the person who entered the data would be interesting for determining other factors and relationships.
The Semantic Web is more or less a variant of first-order logic, for the most part, so the important part is to have a clear understanding of what each of your predicates "mean". This idea is very simple but applicable to a wide-variety of meaning representations - i.e. it is behind the entity model of databases.
There should be no problem representing the information you mentioned in a semantic web representation. Just be sure to have a clear definition of what each of your predicates denote, so that the meaning doesn't shift over time and you end up with an inconsistent representation.
Genesereth's book is old but a good one if you are interested in reading about this in further detail. I think a lot of people who worked on the Semantic Web were involved in Douglas Lenat's Cyc project which gradually shifted to a logic-based meaning representation over time.
http://www.amazon.com/Logical-Foundations-Artificial-Intelligence-Genesereth/dp/0934613311
The site for Cyc:
http://www.cyc.com/
I find designing/selecting data formats is very hard without an understanding of the questions I will be asking using that data. What purpose do you expect the data to be used for? Come up with some use cases and that may guide your search.
Storing attributed data is an open research topic, with development in (among other places) the Intelligence community: these users obviously need to keep track of where information came from, and who has added to it along the way, both to verify its reliability and to do things like track whether Secret information has been included by accident. That may be a good place to look.
Data is data, what you want to do is label the data as what it is, an opinion or a rating. A "fact" I suppose which could be inferred from such data would be that most people had x subjective opinion about said topic.
from twitter:
jimpick #the_real_kevinw Each user and app/base has their own namespace, but I'd ask on the developers mailing list. A mashup might fit better.