PMT is a function in excel for the periodic payment for a loan.

In excel, The Syntax is PMT(rate, nper, pv, [fv], [type])

• Rate    Required. The interest rate for the loan.
• Nper    Required. The total number of payments for the loan.
• Pv    Required. The present value, or the total amount that a series of future payments is worth now; also known as the principal.

Yet, in DAX, there is no built in function yet for PMT. To calculate this we need to reapply for its mathmatic logic.

So, you can use

DAXVersionPMT = ((Pv*Rate))/(1-((1+Rate))^(-1*Nper))))*(-1) 
// Remind: if you are trying to calculate monthly payment but rate is annual rate, then you need to convert to monthly rate by devide to 12

Accumulated Principle = var p=[PV]

var i=[Rate]

var n=[Nper]

var b=[Start_period]

var e=[End_period]

var m=[DAXVersionPMT]*(-1)

var q=12 // if rate is annual rate and you calculated you PMT as monthly period, then you need to convert to monthly rate by devide to 12, if the rate is for monthly rate, then you just need to use q=1

Return ((p-m*q/i)*(1+(i/q))^(e)+m*q/i)-((p-m*q/i)*(1+(i/q))^(b-1)+m*q/i)

Step 1

CREATE PARTITION FUNCTION PF_Fact_test (int)

AS RANGE

LEFT FOR VALUES

(20140101,20150101,20160101);

]

Step 2 

CREATE PARTITION SCHEME [PS_iGPT_FACT] AS PARTITION [PF_iGPT_FACT] TO ([iGPT2014], [iGPT2015], [iGPT2016],[iGPT2017])

Step 3

 Assign Partition Scheme and Partition Funtion to a table

USE [iGPT]

GO

BEGIN TRANSACTION

CREATE CLUSTERED INDEX [ClusteredIndex_on_PS_Fact_Test_636351103815297616] ON [dbo].[iGPTextraInfo]

([MaxDateAces])WITH (SORT_IN_TEMPDB = OFF, DROP_EXISTING = OFF, ONLINE = OFF) ON [PS_Fact_Test]([MaxDateAces])

DROP INDEX [ClusteredIndex_on_PS_Fact_Test_636351103815297616] ON [dbo].[iGPTextraInfo]

COMMIT TRANSACTION

Step 4

Load data into the partitioned table

 –The following query returns one or more rows if the table PartitionTable is partitioned

SELECT *

FROM sys.tables AS t

JOIN sys.indexes AS i

ON t.[object_id] = i.[object_id]

AND i.[type] IN (0,1)

JOIN sys.partition_schemes ps

ON i.data_space_id = ps.data_space_id

WHERE t.name = ‘GPTClaimPendedFact’;

— The following query returns the boundary values for each partition in the PartitionTable table.

SELECT t.name AS TableName, i.name AS IndexName, p.partition_number,p.rows AS Rows, p.partition_id, i.data_space_id, f.function_id, f.type_desc, r.boundary_id, r.value AS BoundaryValue

FROM sys.tables AS t

JOIN sys.indexes AS i

ON t.object_id = i.object_id

JOIN sys.partitions AS p

ON i.object_id = p.object_id AND i.index_id = p.index_id

JOIN sys.partition_schemes AS s

ON i.data_space_id = s.data_space_id

JOIN sys.partition_functions AS f

ON s.function_id = f.function_id

LEFT JOIN sys.partition_range_values AS r

ON f.function_id = r.function_id and r.boundary_id = p.partition_number

WHERE t.name = ‘iGPTInquiryFact_WGS’ AND i.type <= 1

ORDER BY p.partition_number;

–The following query returns the name of the partitioning column for table. PartitionTable.

SELECT

t.[object_id] AS ObjectID

, t.name AS TableName

, ic.column_id AS PartitioningColumnID

, c.name AS PartitioningColumnName

FROM sys.tables AS t

JOIN sys.indexes AS i                           ON t.[object_id] = i.[object_id]  AND i.[type] <= 1 — clustered index or a heap

JOIN sys.partition_schemes AS ps  ON ps.data_space_id = i.data_space_id

JOIN sys.index_columns AS ic             ON ic.[object_id] = i.[object_id]  AND ic.index_id = i.index_id   AND ic.partition_ordinal >= 1 — because 0 = non-partitioning column

JOIN sys.columns AS c                           ON t.[object_id] = c.[object_id]   AND ic.column_id = c.column_id

WHERE t.name = ‘GPTClaimPendedFact’ ;

SELECT row_count              ,*

FROM sys.dm_db_partition_stats

WHERE object_id = OBJECT_ID(‘dbo.GPTClaimPendedFact’) –and row_count > 0

order by partition_number

SELECT * FROM sys.dm_db_partition_stats;

SELECT SUM(used_page_count) AS total_number_of_used_pages,

SUM (row_count) AS total_number_of_rows

FROM sys.dm_db_partition_stats

WHERE object_id=OBJECT_ID(‘dbo.GPTClaimPendedFact’)    AND (index_id=0 or index_id=1);

SQL Server 2016 Analysis Services (SSAS)*, Power Pivot in Excel 2016, and Power BI Desktop include the following new Data Analysis Expressions (DAX) functions:

Date and Time Functions

CALENDAR Function
CALENDARAUTO Function
DATEDIFF Function

Information Functions

ISEMPTY Function
ISONORAFTER Function

Filter Functions

ADDMISSINGITEMS Function
SUBSTITUTEWITHINDEX Function

Math and Trig Functions

ACOS Function
ACOSH Function
ASIN Function
ASINH Function
ATAN Function
ATANH Function
COMBIN Function
COMBINA Function
COS Function
COSH Function
DEGREES Function
EVEN Function
EXP Function
GCD Function
ISO.CEILING Function
LCM Function
MROUND Function
ODD Function
PI Function
PRODUCT Function
PRODUCTX Function
QUOTIENT Function
RADIANS Function
SIN Function
SINH Function
SQRTPI Function
TAN Function
TANH Function

Statistical Functions

BETA.DIST Function
BETA.INV Function
CHISQ.INV Function
CHISQ.INV.RT Function
CONFIDENCE.NORM Function
CONFIDENCE.T Function
EXPON.DIST Function
GEOMEAN Function
GEOMEANX Function
MEDIAN Function
MEDIANX Function
PERCENTILE.EXC Function
PERCENTILE.INC Function
PERCENTILEX.EXC Function
PERCENTILEX.INC Function
SELECTCOLUMNS Function
XIRR Function
XNPV Function

Text Functions

CONCATENATEX Function

Other Functions

GROUPBY Function
INTERSECT Function
NATURALINNERJOIN Function
NATURALLEFTOUTERJOIN Function
SUMMARIZECOLUMNS Function
UNION Function
VAR

Today, I would like to talk about the different roles in a typical BI project. Like all technology-related initiatives, it is vital to assign clear responsibilities and distinguish different responsibilities in order to achieve a successful BI project result.

• Project Manager – This role is needed to understand the overall scope of the BI project including the objectives, timeline, budget, and resources. Based on these parameters, they will need to work with other individuals within the project team to come up with timelines and resource assignments. During the development phase, he/she will monitor the project’s progress and make adjustments as needed.
• BI Solution Architect – This person will be in charge of the overall design of the data warehouse. They will focus on creating the vision of the entire BI process, development and lifecycle. They will work directly with business users and the project manager to design actionable insights while concurrently working with the ETL developer, DBAs, and Data Modelers to break down the vision into detailed actionable tasks.
• Data modelers – The Data Modelers will be responsible with the design of the data warehouse schema and the data models. They need to understand the business requirements, the vision produced by the BI solutions architect, and the physical capabilities of the environment. In addition, the will be responsible for creating the data warehouse schema, the ETL requirements, the data models, and the design model processing schedules.’
• Database Administrators (DBA) – These individuals will be in charge of designing the physical Database Architecture and configuration, security settings, as well as data source identification and data source management.
• Infrastructure Specialists – These individuals are responsible for ensuring that the servers and networks are set up correctly to meet the current and future requirements. They will also be responsible for the server upgrade and migration.
• ETL Developers – The ETL Developers are responsible for building the workflows from external source to the Data Warehouse. They will be working closely with the DBAs and Data modelers to understand the source and target form of the data as well as the timing of ETL workflows.
• Report developers – These individuals, of all the other roles, work closest with the business users. Their role is to work with business users to design the reports and schedule automated report generation while providing the data modelers with future model requirements.
• Business users – These individuals provide requirements to the BI development team. They provide initial abstract pertaining to what they want at the beginning of the project. As prototype products come out, these abstracts become more detailed and final.
• Testers – Testers are responsible for Unit Testing, Integration Testing, Functional Testing, and Systems Testing. Performance Testing, Usability Testing and Acceptance Testing.

(https://www.codeproject.com/Tips/351122/What-is-software-testing-What-are-the-different-ty)

Often time, all the project team members work closely with each other. Usually, for a large project, one or more team members will wear multiple hats pertaining the roles above. In smaller BI teams, one person may play different roles. Although this may create some extra burden in terms of workload, it reduces the onerous need for establishing communication between different persons. I usually see the BI solution architect, data modeler and ETL developer to be one person at the beginning of the development phase and as the project grows, that person will begin outsourcing his/her roles to other team members.

Thanks,

Your friend – Annie

A key to understanding DAX is to distinguish Filter Context and Row Context.

Here are definitions of each context.

Filter Context: can be simply defines as filter context the set of filters applied to the evaluation of a DAX expression, usually a measure, regardless of how they have been generated. Usually, every cell of a report has a different filter context, which can be defined implicitly by the user interface (such as the pivot table in Excel), or explicitly by some DAX expression using CALCULATE or CALCULATETABLE. Filter Context always exist before a DAX expression been evaluated.

Row Context: the concept of row context is always exist in a DAX expression. In order to get the value of a DAX expression, you need a way to tell DAX the row to use AKA checking the current row of a table and provide the value back. You have a row context whenever you iterate a table, either explicitly (using an iterator) or implicitly (in a calculated column).

Use one DAX measure as an Example:

SumofProductSalesAmount:=SUMX(

VALUES([Product].[ProductName]),   

CALCULATE (

        [Sales Amount]

    )

)

Explain in detail of this calculation:

1. VALUES Function returns a table, meaning it provide All the Distinctive ProductName back as a table outcome
2. SUMX iterate each row of the table in its first argument, then it aggregate the value each row returns in sum. In this case, for each row of a table which provided by VALUES function AKA for each product, it calculate the value in the second argument of the SUMX function. Then, Sum all the value together and return back to the caller.
3. Things happens outside CALCULATE Function are all treated as Filter Context of the CALCULATE expression. In this case, there are two places feeding the CACULATE section with Filter Context.
   • First place is, the Current Row defined by SUMX, in our case, it is the Current Row of VALUES([Product].[ProductName]) which will be a specific Product depends on where the iterator at. Meaning Evaluated [Sales Amount] Measure with a filter which limit to a certain Product, and then provide the value (sales amount) back.
   • Second Place is, whenever this measure [SumofProductSalesAmount] exposed in a cell user application (like Excel, PowerBI, SSRS), it exposed in a filter context set on that specific Cell. Depends on wherever your cell is at you have different filter context. For example you may have a filter on a cell to limit the time frame to 2017, etc.

Thanks,

Your friend – Annie.