It’s been some time that I’m working with OData information supply in Energy BI. One problem that I virtually at all times wouldn’t have an excellent understanding of the underlying information mannequin. It may be actually onerous and time consuming if there isn’t a one within the enterprise that understands the underlying information mannequin. I do know, we will use $metadata to get the metadata schema from the OData feed, however let’s not go there. I’m not an OData professional however right here is the factor for somebody like me, I work with varied information sources which I’m not essentially an professional in, however I would like to grasp what the entities are, how they’re related and many others… then what if I wouldn’t have entry any SMEs (Subject Matter Expert) who may also help me with that?
So getting concerned with extra OData choices, let’s get into it.
The customized perform under accepts an OData URL then it discovers all tables, their column rely, their row rely (extra on this later), quantity and record of associated tables, quantity and record of columns of kind textual content, kind quantity and Decimal.Sort.
// fnODataFeedAnalyser
(ODataFeed as textual content) =>
let
Supply = OData.Feed(ODataFeed),
SourceToTable = Desk.RenameColumns(
Desk.DemoteHeaders(Desk.FromValue(Supply)),
{{"Column1", "Title"}, {"Column2", "Information"}}
),
FilterTables = Desk.SelectRows(
SourceToTable,
every Sort.Is(Worth.Sort([Data]), Desk.Sort) = true
),
SchemaAdded = Desk.AddColumn(FilterTables, "Schema", every Desk.Schema([Data])),
TableColumnCountAdded = Desk.AddColumn(
SchemaAdded,
"Desk Column Rely",
every Desk.ColumnCount([Data]),
Int64.Sort
),
TableCountRowsAdded = Desk.AddColumn(
TableColumnCountAdded,
"Desk Row Rely",
every Desk.RowCount([Data]),
Int64.Sort
),
NumberOfRelatedTablesAdded = Desk.AddColumn(
TableCountRowsAdded,
"Variety of Associated Tables",
every Listing.Rely(Desk.ColumnsOfType([Data], {Desk.Sort}))
),
ListOfRelatedTables = Desk.AddColumn(
NumberOfRelatedTablesAdded,
"Listing of Associated Tables",
every
if [Number of Related Tables] = 0 then
null
else
Desk.ColumnsOfType([Data], {Desk.Sort}),
Listing.Sort
),
NumberOfTextColumnsAdded = Desk.AddColumn(
ListOfRelatedTables,
"Variety of Textual content Columns",
every Listing.Rely(Desk.SelectRows([Schema], every Textual content.Accommodates([Kind], "textual content"))[Name]),
Int64.Sort
),
ListOfTextColunmsAdded = Desk.AddColumn(
NumberOfTextColumnsAdded,
"Listing of Textual content Columns",
every
if [Number of Text Columns] = 0 then
null
else
Desk.SelectRows([Schema], every Textual content.Accommodates([Kind], "textual content"))[Name]
),
NumberOfNumericColumnsAdded = Desk.AddColumn(
ListOfTextColunmsAdded,
"Variety of Numeric Columns",
every Listing.Rely(Desk.SelectRows([Schema], every Textual content.Accommodates([Kind], "quantity"))[Name]),
Int64.Sort
),
ListOfNumericColunmsAdded = Desk.AddColumn(
NumberOfNumericColumnsAdded,
"Listing of Numeric Columns",
every
if [Number of Numeric Columns] = 0 then
null
else
Desk.SelectRows([Schema], every Textual content.Accommodates([Kind], "quantity"))[Name]
),
NumberOfDecimalColumnsAdded = Desk.AddColumn(
ListOfNumericColunmsAdded,
"Variety of Decimal Columns",
every Listing.Rely(
Desk.SelectRows([Schema], every Textual content.Accommodates([TypeName], "Decimal.Sort"))[Name]
),
Int64.Sort
),
ListOfDcimalColunmsAdded = Desk.AddColumn(
NumberOfDecimalColumnsAdded,
"Listing of Decimal Columns",
every
if [Number of Decimal Columns] = 0 then
null
else
Desk.SelectRows([Schema], every Textual content.Accommodates([TypeName], "Decimal.Sort"))[Name]
),
#"Eliminated Different Columns" = Desk.SelectColumns(
ListOfDcimalColunmsAdded,
{
"Title",
"Desk Column Rely",
"Desk Row Rely",
"Variety of Associated Tables",
"Listing of Associated Tables",
"Variety of Textual content Columns",
"Listing of Textual content Columns",
"Variety of Numeric Columns",
"Listing of Numeric Columns",
"Variety of Decimal Columns",
"Listing of Decimal Columns"
}
)
in
#"Eliminated Different Columns"
Right here is the GitHub hyperlink for the above code.
I used this perform for preliminary investigation on varied OData sources together with Microsoft Mission On-line, Microsoft Enterprise Central, some third occasion instruments and naturally Northwind pattern. Whereas it really works superb in the entire talked about information sources, for some information sources like Enterprise Central it isn’t fairly useful. So be conscious of that.
I used Energy Question formatter to format the above code. I simply polished it a bit to suit it to my style. Give it a go, it’s an excellent device.
As talked about earlier, the above perform exhibits tables’ column rely in addition to their row rely. On the latter, the row rely, I wish to increase some extent. If the underlying desk has lots of columns then the row rely calculation could take a very long time.
The screenshot under exhibits the outcomes of the fnODataFeedAnalyser perform invoked for a Microsoft Mission On-line and it took a wee bit lower than 3 minutes to run.
fnODataFeedAnalyser customized perform for Microsoft Mission On-lineHave you ever used this technique earlier than to analyse a dataset that you’re not accustomed to the construction? Do have a greater thought? Please share your ideas within the feedback part under.
Oh! and… by the best way, be at liberty to vary the above code and make it higher. Simply don’t forget to share the improved model with the neighborhood.
