5.1.4 Queries, queries, queries… and churn analysis
Objective
- Write queries for data analyses
- Write SQL queries combining online, call center and loyalty data available in ۶Ƶ Experience Platform
- Learn about ۶Ƶ Defined Functions
Context
In this exercises you will write queries to analyze product views, product funnels, churn etc.
All queries listed in this chapter will be executed in your PSQL command-line interface. You should copy (CTRL-c) the statement blocks indicated with SQL and paste (CTRL-v)them in the PSQL command-line interface. The Query Result blocks show the pasted SQL statement and the associated query result.
Write basic queries for data analysis
Timestamp
Data captured in ۶Ƶ Experience Platform is time stamped. The timestamp attribute allows you to analyze data over time.
How many product views do we have on a daily basis?
SQL
select date_format( timestamp , 'yyyy-MM-dd') AS Day,
count(*) AS productViews
from demo_system_event_dataset_for_website_global_v1_1
where --aepTenantId--.demoEnvironment.brandName IN ('Citi Signal')
and eventType = 'commerce.productViews'
group by Day
limit 10;
Copy the statement above and execute it in your PSQL command-line interface.
Query Result
tech-insiders:all=> select date_format( timestamp , 'yyyy-MM-dd') AS Day,
count(*) AS productViews
from demo_system_event_dataset_for_website_global_v1_1
where _experienceplatform.demoEnvironment.brandName IN ('Citi Signal')
and eventType = 'commerce.productViews'
group by Day
limit 10;
Day | productViews
------------+--------------
2024-12-04 | 2297
(1 row)
Top 5 products viewed
What are the top 5 products viewed?
SQL
select productListItems.name, count(*)
from demo_system_event_dataset_for_website_global_v1_1
where --aepTenantId--.demoEnvironment.brandName IN ('Citi Signal')
and eventType = 'commerce.productViews'
group by productListItems.name
order by 2 desc
limit 5;
Copy the statement above and execute it in your PSQL command-line interface.
Query Result
tech-insiders:all=> select productListItems.name, count(*)
from demo_system_event_dataset_for_website_global_v1_1
where _experienceplatform.demoEnvironment.brandName IN ('Citi Signal')
and eventType = 'commerce.productViews'
group by productListItems.name
order by 2 desc
limit 5;
name | count(1)
-----------------------------------------+----------
{Google Pixel XL 32GB Black Smartphone} | 938
{SIM Only} | 482
{Samsung Galaxy S8} | 456
{Samsung Galaxy S7 32GB Black} | 421
(4 rows)
Product Interaction funnel, from viewing to buying
SQL
select eventType, count(*)
from demo_system_event_dataset_for_website_global_v1_1
where --aepTenantId--.demoEnvironment.brandName IN ('Citi Signal')
and eventType is not null
and eventType <> ''
group by eventType;
Copy the statement above and execute it in your PSQL command-line interface.
Query Result
tech-insiders:all=> select eventType, count(*)
from demo_system_event_dataset_for_website_global_v1_1
where _experienceplatform.demoEnvironment.brandName IN ('Citi Signal')
and eventType is not null
and eventType <> ''
group by eventType;
eventType | count(1)
--------------------------+----------
commerce.productListAdds | 494
commerce.purchases | 246
commerce.productViews | 2297
(3 rows)
Identify visitors with risk to Churn (visit page => Cancel Service)
SQL
select distinct --aepTenantId--.identification.core.ecid
from demo_system_event_dataset_for_website_global_v1_1
where --aepTenantId--.demoEnvironment.brandName IN ('Citi Signal')
and web.webPageDetails.name = 'Cancel Service'
group by --aepTenantId--.identification.core.ecid
limit 10;
Copy the statement above and execute it in your PSQL command-line interface.
Query Result
tech-insiders:all=> select distinct _experienceplatform.identification.core.ecid
from demo_system_event_dataset_for_website_global_v1_1
where _experienceplatform.demoEnvironment.brandName IN ('Citi Signal')
and web.webPageDetails.name = 'Cancel Service'
group by _experienceplatform.identification.core.ecid
limit 10;
ecid
----------------------------------
86069928882940477620713284798772
75691756152042231410852704832434
47381264398548915586824480724480
51294194577949645447313762862726
95873885060131472480685538836534
71192995127345419624952514250737
81469709164961922907426138040032
53545252726821876244061095202780
13294750130353985087337266864522
58843891994459565443501421307174
(10 rows)
In the next set of queries we will extend the above query, in order to get a complete view on the customers and their behavior that have been visiting the “Cancel Service” page. You will learn how to use the ۶Ƶ Defined Function to sessionize information, identify the sequence and timing of events. You will also join datasets together to further enrich and prepare the data for analysis in Microsoft Power BI.
Advanced Queries
The majority of the business logic requires gathering the touch-points for a customer and ordering them by time. This support is provided by Spark SQL in the form of window functions. Window functions are part of standard SQL and are supported by many other SQL engines.
۶Ƶ Defined Functions
۶Ƶ has added a set of ۶Ƶ Defined Functions to the standard SQL syntax that allow you to better understand your experience data. In the next couple of queries you will learn about these ADF functions. You can find more information and the complete list in the documentation.
What do people do on the site before reaching the “Cancel Service” page as the 3rd page in a session?
With this query you will discover the first two ۶Ƶ Defined Functions SESS_TIMEOUT and NEXT
The SESS_TIMEOUT() reproduces the visit groupings found with ۶Ƶ Analytics. It performs a similar time-based grouping, but customizable parameters.
NEXT() and PREVIOUS() help you to understand how customers navigate your site.
SQL
SELECT
webPage,
webPage_2,
webPage_3,
webPage_4,
count(*) journeys
FROM
(
SELECT
webPage,
NEXT(webPage, 1, true)
OVER(PARTITION BY ecid, session.num
ORDER BY timestamp
ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING).value
AS webPage_2,
NEXT(webPage, 2, true)
OVER(PARTITION BY ecid, session.num
ORDER BY timestamp
ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING).value
AS webPage_3,
NEXT(webPage, 3, true)
OVER(PARTITION BY ecid, session.num
ORDER BY timestamp
ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING).value
AS webPage_4,
session.depth AS SessionPageDepth
FROM (
select a.--aepTenantId--.identification.core.ecid as ecid,
a.timestamp,
web.webPageDetails.name as webPage,
SESS_TIMEOUT(timestamp, 60 * 30)
OVER (PARTITION BY a.--aepTenantId--.identification.core.ecid
ORDER BY timestamp
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)
AS session
from demo_system_event_dataset_for_website_global_v1_1 a
where a.--aepTenantId--.identification.core.ecid in (
select b.--aepTenantId--.identification.core.ecid
from demo_system_event_dataset_for_website_global_v1_1 b
where b.--aepTenantId--.demoEnvironment.brandName IN ('Citi Signal')
and b.web.webPageDetails.name = 'Cancel Service'
)
)
)
WHERE SessionPageDepth=1
and webpage_3 = 'Cancel Service'
GROUP BY webPage, webPage_2, webPage_3, webPage_4
ORDER BY journeys DESC
LIMIT 10;
Copy the statement above and execute it in your PSQL command-line interface.
Query Result
webPage | webPage_2 | webPage_3 | webPage_4 | journeys
---------------------------------------+---------------------------------------+----------------+------------+----------
Telco Home | Citi Signal Sport | Cancel Service | Call Start | 2
Citi Signal Sport | Google Pixel XL 32GB Black Smartphone | Cancel Service | Call Start | 2
Broadband Deals | Samsung Galaxy S7 32GB Black | Cancel Service | | 2
TV & Broadband Deals | Samsung Galaxy S7 32GB Black | Cancel Service | | 2
SIM Only | Citi Signal Shop | Cancel Service | | 2
Google Pixel XL 32GB Black Smartphone | Broadband Deals | Cancel Service | | 2
SIM Only | Telco Home | Cancel Service | | 2
Citi Signal Shop | Samsung Galaxy S7 32GB Black | Cancel Service | Call Start | 1
Google Pixel XL 32GB Black Smartphone | Citi Signal Sport | Cancel Service | Call Start | 1
Google Pixel XL 32GB Black Smartphone | Citi Signal Shop | Cancel Service | Call Start | 1
(10 rows)
How much time do we have before a visitor calls the call center after visiting the “Cancel Service” Page?
To answer this kind of query will we use the TIME_BETWEEN_NEXT_MATCH() ۶Ƶ Defined Function.
Time-between previous or next match functions provide a new dimension, which measures the time that has elapsed since a particular incident.
SQL
select * from (
select --aepTenantId--.identification.core.ecid as ecid,
web.webPageDetails.name as webPage,
TIME_BETWEEN_NEXT_MATCH(timestamp, web.webPageDetails.name='Call Start', 'seconds')
OVER(PARTITION BY --aepTenantId--.identification.core.ecid
ORDER BY timestamp
ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING)
AS contact_callcenter_after_seconds
from demo_system_event_dataset_for_website_global_v1_1
where --aepTenantId--.demoEnvironment.brandName IN ('Citi Signal')
and web.webPageDetails.name in ('Cancel Service', 'Call Start')
) r
where r.webPage = 'Cancel Service'
limit 15;
Copy the statement above and execute it in your PSQL command-line interface.
Query Result
ecid | webPage | contact_callcenter_after_seconds
----------------------------------+----------------+----------------------------------
00331886620679939148047665693117 | Cancel Service |
00626561600197295782131349716866 | Cancel Service |
00630470663554417679969244202779 | Cancel Service | -797
00720875344152796154458668700428 | Cancel Service | -519
00746064605049656090779523644276 | Cancel Service | -62
00762093837616944422322357210965 | Cancel Service |
00767875779073091876070699689209 | Cancel Service |
00798691264980137616449378075855 | Cancel Service |
00869613691740150556826953447162 | Cancel Service | -129
00943638725078228957873279219207 | Cancel Service | -750
01167540466536077846425644389346 | Cancel Service |
01412448537869549016063764484810 | Cancel Service |
01419076946514450291741574452702 | Cancel Service | -482
01533124771963987423015507880755 | Cancel Service |
01710651086750904478559809475925 | Cancel Service |
(15 rows)
And what is the outcome of that contact?
In this query, you’ll be joining datasets together. In this case you’ll join the dataset demo_system_event_dataset_for_website_global_v1_1 with the datasetdemo_system_event_dataset_for_call_center_global_v1_1. This is done to understand the outcome of the call center interaction.
SQL
select distinct r.*,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callFeeling,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callTopic,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callContractCancelled
from (
select --aepTenantId--.identification.core.ecid ecid,
web.webPageDetails.name as webPage,
TIME_BETWEEN_NEXT_MATCH(timestamp, web.webPageDetails.name='Call Start', 'seconds')
OVER(PARTITION BY --aepTenantId--.identification.core.ecid
ORDER BY timestamp
ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING)
AS contact_callcenter_after_seconds
from demo_system_event_dataset_for_website_global_v1_1
where --aepTenantId--.demoEnvironment.brandName IN ('Citi Signal')
and web.webPageDetails.name in ('Cancel Service', 'Call Start')
) r
, demo_system_event_dataset_for_call_center_global_v1_1 c
where r.ecid = c.--aepTenantId--.identification.core.ecid
and r.webPage = 'Cancel Service'
and c.--aepTenantId--.interactionDetails.core.callCenterAgent.callContractCancelled IN (true,false)
and c.--aepTenantId--.interactionDetails.core.callCenterAgent.callTopic IN ('contract', 'invoice','complaint','wifi')
limit 15;
Copy the statement above and execute it in your PSQL command-line interface.
Query Result
ecid | webPage | contact_callcenter_after_seconds | callfeeling | calltopic | callcontractcancelled
----------------------------------+----------------+----------------------------------+-------------+-----------+-----------------------
00630470663554417679969244202779 | Cancel Service | -797 | negative | contract | f
00720875344152796154458668700428 | Cancel Service | -519 | positive | contract | f
00746064605049656090779523644276 | Cancel Service | -62 | positive | contract | t
00869613691740150556826953447162 | Cancel Service | -129 | negative | contract | t
00943638725078228957873279219207 | Cancel Service | -750 | positive | contract | f
01419076946514450291741574452702 | Cancel Service | -482 | neutral | contract | f
01738842540109643781526526573341 | Cancel Service | -562 | neutral | contract | f
02052460258994877317679083617975 | Cancel Service | -545 | neutral | contract | f
02156496759733199802585567179589 | Cancel Service | -83 | neutral | contract | t
02666934104296797891818818456669 | Cancel Service | -297 | positive | contract | t
03059764265715537001416957172652 | Cancel Service | -243 | negative | contract | t
03347899869945278660479273416679 | Cancel Service | -229 | positive | contract | t
04258863338643046907489131372300 | Cancel Service | -588 | positive | contract | f
04733864373954008966920919247566 | Cancel Service | -795 | neutral | contract | f
05199871096822598772351169572451 | Cancel Service | -236 | positive | contract | t
(15 rows)
What is the loyalty profile of these customers?
In this query we join CRM data that was onboarded in ۶Ƶ Experience Platform. This makes it possible to enrich the churn analysis with CRM data.
SQL
select r.*,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callFeeling,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callTopic,
l.--aepTenantId--.loyaltyDetails.level,
l.--aepTenantId--.identification.core.crmId
from (
select --aepTenantId--.identification.core.ecid ecid,
web.webPageDetails.name as webPage,
TIME_BETWEEN_NEXT_MATCH(timestamp, web.webPageDetails.name='Call Start', 'seconds')
OVER(PARTITION BY --aepTenantId--.identification.core.ecid
ORDER BY timestamp
ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING)
AS contact_callcenter_after_seconds
from demo_system_event_dataset_for_website_global_v1_1
where --aepTenantId--.demoEnvironment.brandName IN ('Citi Signal')
and web.webPageDetails.name in ('Cancel Service', 'Call Start')
) r
, demo_system_event_dataset_for_call_center_global_v1_1 c
, demo_system_profile_dataset_for_crm_global_v1_1 l
where r.ecid = c.--aepTenantId--.identification.core.ecid
and r.webPage = 'Cancel Service'
and l.--aepTenantId--.identification.core.ecid = r.ecid
and c.--aepTenantId--.interactionDetails.core.callCenterAgent.callTopic IN ('contract', 'invoice','complaint','wifi','promo')
limit 15;
Copy the statement above and execute it in your PSQL command-line interface.
Query Result
ecid | webPage | contact_callcenter_after_seconds | callfeeling | calltopic | level | crmid
----------------------------------+----------------+----------------------------------+-------------+-----------+--------+-----------
00630470663554417679969244202779 | Cancel Service | -797 | negative | contract | Bronze | 524483285
00720875344152796154458668700428 | Cancel Service | -519 | positive | contract | Silver | 860696333
00746064605049656090779523644276 | Cancel Service | -62 | positive | contract | Bronze | 072387270
00869613691740150556826953447162 | Cancel Service | -129 | negative | contract | Bronze | 789347684
00943638725078228957873279219207 | Cancel Service | -750 | positive | contract | Gold | 033926162
01419076946514450291741574452702 | Cancel Service | -482 | neutral | contract | Bronze | 105063634
01738842540109643781526526573341 | Cancel Service | -562 | neutral | contract | Gold | 791324509
02052460258994877317679083617975 | Cancel Service | -545 | neutral | contract | Gold | 443477555
02156496759733199802585567179589 | Cancel Service | -83 | neutral | contract | Silver | 305085589
02666934104296797891818818456669 | Cancel Service | -297 | positive | contract | Silver | 104266570
03059764265715537001416957172652 | Cancel Service | -243 | negative | contract | Silver | 814175245
03347899869945278660479273416679 | Cancel Service | -229 | positive | contract | Gold | 377699708
04258863338643046907489131372300 | Cancel Service | -588 | positive | contract | Silver | 298321657
04733864373954008966920919247566 | Cancel Service | -795 | neutral | contract | Gold | 655070958
05199871096822598772351169572451 | Cancel Service | -236 | positive | contract | Gold | 425688874
(15 rows)
From what region do they visit us?
Lets include the geographical info, like longitude, attitude, city, countrycode, captured by the ۶Ƶ Experience Platform in order to get some geographical insights about churning customers.
SQL
select distinct r.ecid,
r.city,
r.countrycode,
r.lat as latitude,
r.lon as longitude,
r.contact_callcenter_after_seconds as seconds_to_contact_callcenter,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callFeeling,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callTopic,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callContractCancelled,
l.--aepTenantId--.loyaltyDetails.level,
l.--aepTenantId--.identification.core.crmId
from (
select --aepTenantId--.identification.core.ecid ecid,
placeContext.geo._schema.latitude lat,
placeContext.geo._schema.longitude lon,
placeContext.geo.city,
placeContext.geo.countryCode,
web.webPageDetails.name as webPage,
TIME_BETWEEN_NEXT_MATCH(timestamp, web.webPageDetails.name='Call Start', 'seconds')
OVER(PARTITION BY --aepTenantId--.identification.core.ecid
ORDER BY timestamp
ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING)
AS contact_callcenter_after_seconds
from demo_system_event_dataset_for_website_global_v1_1
where --aepTenantId--.demoEnvironment.brandName IN ('Citi Signal')
and web.webPageDetails.name in ('Cancel Service', 'Call Start')
) r
, demo_system_event_dataset_for_call_center_global_v1_1 c
, demo_system_profile_dataset_for_crm_global_v1_1 l
where r.ecid = c.--aepTenantId--.identification.core.ecid
and r.webPage = 'Cancel Service'
and l.--aepTenantId--.identification.core.ecid = r.ecid
and c.--aepTenantId--.interactionDetails.core.callCenterAgent.callTopic IN ('contract', 'invoice','complaint','wifi','promo')
limit 15;
Copy the statement above and execute it in your PSQL command-line interface.
Query Result
ecid | city | countrycode | latitude | longitude | seconds_to_contact_callcenter | callfeeling | calltopic | callcontractcancelled | level | crmid
----------------------------------+------------+-------------+------------+------------+-------------------------------+-------------+-----------+-----------------------+--------+-----------
00630470663554417679969244202779 | Charlton | GB | 51.59119 | -1.407848 | -797 | negative | contract | f | Bronze | 524483285
00720875344152796154458668700428 | Ashley | GB | 51.4139633 | -2.2685462 | -519 | positive | contract | f | Silver | 860696333
00746064605049656090779523644276 | Liverpool | GB | 53.4913801 | -2.867264 | -62 | positive | contract | t | Bronze | 072387270
00869613691740150556826953447162 | Langley | GB | 51.888151 | -0.23924 | -129 | negative | contract | t | Bronze | 789347684
00943638725078228957873279219207 | Eaton | GB | 53.2945961 | -0.9335791 | -750 | positive | contract | f | Gold | 033926162
01419076946514450291741574452702 | Tullich | GB | 57.4694803 | -3.1269422 | -482 | neutral | contract | f | Bronze | 105063634
01738842540109643781526526573341 | Whitwell | GB | 54.3886617 | -1.555363 | -562 | neutral | contract | f | Gold | 791324509
02052460258994877317679083617975 | Edinburgh | GB | 55.9309486 | -3.1859102 | -545 | neutral | contract | f | Gold | 443477555
02156496759733199802585567179589 | West End | GB | 53.46464 | 0.04134 | -83 | neutral | contract | t | Silver | 305085589
02666934104296797891818818456669 | Newtown | GB | 51.3684218 | -1.3218754 | -297 | positive | contract | t | Silver | 104266570
03059764265715537001416957172652 | Edinburgh | GB | 55.9309486 | -3.1859102 | -243 | negative | contract | t | Silver | 814175245
03347899869945278660479273416679 | Liverpool | GB | 53.4913801 | -2.867264 | -229 | positive | contract | t | Gold | 377699708
04258863338643046907489131372300 | Norton | GB | 52.2679288 | -1.1202549 | -588 | positive | contract | f | Silver | 298321657
04733864373954008966920919247566 | Whitchurch | GB | 51.4057505 | -2.5573746 | -795 | neutral | contract | f | Gold | 655070958
05199871096822598772351169572451 | Stapleford | GB | 53.10672 | -0.687802 | -236 | positive | contract | t | Gold | 425688874
(15 rows)
Call Center Interaction Analysis
In the queries above we only looked at the visitors that ended up contacting the call center in case of service cancellation. We want to take this a bit broader and take into account all call center interaction including (wifi, promo, invoice, complaint and contract).
You will need to edit a query, so let’s first open notepad or brackets.
On Windows click “search”-icon (1) in the windows toolbar, type notepad in the “search”-field (2), click (3) the “notepad” result:
On Mac
Copy the following statement to notepad/brackets:
select /* enter your name */
e.--aepTenantId--.identification.core.ecid as ecid,
e.placeContext.geo.city as city,
e.placeContext.geo._schema.latitude latitude,
e.placeContext.geo._schema.longitude longitude,
e.placeContext.geo.countryCode as countrycode,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callFeeling as callFeeling,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callTopic as callTopic,
c.--aepTenantId--.interactionDetails.core.callCenterAgent.callContractCancelled as contractCancelled,
l.--aepTenantId--.loyaltyDetails.level as loyaltystatus,
l.--aepTenantId--.loyaltyDetails.points as loyaltypoints,
l.--aepTenantId--.identification.core.crmId as crmid
from demo_system_event_dataset_for_website_global_v1_1 e
,demo_system_event_dataset_for_call_center_global_v1_1 c
,demo_system_profile_dataset_for_crm_global_v1_1 l
where e.--aepTenantId--.demoEnvironment.brandName IN ('Citi Signal')
and e.web.webPageDetails.name in ('Cancel Service', 'Call Start')
and e.--aepTenantId--.identification.core.ecid = c.--aepTenantId--.identification.core.ecid
and l.--aepTenantId--.identification.core.ecid = e.--aepTenantId--.identification.core.ecid;
And replace
enter your name
Do not remove /\* and \*/. Your modified statement in notepad should look like:
Copy your modified statement from notepad into the PSQL command line window and hit enter. You should see the following result in the PSQL command line window:
tech-insiders:all=> select /* vangeluw */
e._experienceplatform.identification.core.ecid as ecid,
e.placeContext.geo.city as city,
e.placeContext.geo._schema.latitude latitude,
e.placeContext.geo._schema.longitude longitude,
e.placeContext.geo.countryCode as countrycode,
c._experienceplatform.interactionDetails.core.callCenterAgent.callFeeling as callFeeling,
c._experienceplatform.interactionDetails.core.callCenterAgent.callTopic as callTopic,
c._experienceplatform.interactionDetails.core.callCenterAgent.callContractCancelled as contractCancelled,
l._experienceplatform.loyaltyDetails.level as loyaltystatus,
l._experienceplatform.loyaltyDetails.points as loyaltypoints,
l._experienceplatform.identification.core.crmId as crmid
from demo_system_event_dataset_for_website_global_v1_1 e
,demo_system_event_dataset_for_call_center_global_v1_1 c
,demo_system_profile_dataset_for_crm_global_v1_1 l
where e._experienceplatform.demoEnvironment.brandName IN ('Citi Signal')
and e.web.webPageDetails.name in ('Cancel Service', 'Call Start')
and e._experienceplatform.identification.core.ecid = c._experienceplatform.identification.core.ecid
and l._experienceplatform.identification.core.ecid = e._experienceplatform.identification.core.ecid;
ecid | city | latitude | longitude | countrycode | callFeeling | callTopic | contractCancelled | loyaltystatus | loyaltypoints | crmid
----------------------------------+------------+------------+------------+-------------+-------------+-----------+-------------------+---------------+---------------+-----------
60082543727227001177187726544992 | Normanton | 52.643749 | -0.622129 | GB | neutral | contract | f | Bronze | 430.0 | 117969439
03250145103029549687906576330844 | Charlton | 51.59119 | -1.407848 | GB | none | none | f | Silver | 585.0 | 271570836
87322786414150971711720565798532 | Whitwell | 54.3886617 | -1.555363 | GB | none | none | f | Bronze | 872.0 | 570762160
46736059905281823751180777497223 | Edinburgh | 55.9309486 | -3.1859102 | GB | none | none | f | Gold | 482.0 | 980678773
81958524709959359235057647680790 | Linton | 54.0542238 | -2.0215836 | GB | none | none | f | Bronze | 666.0 | 341873673
24854602977644353049269284436324 | Tullich | 57.4694803 | -3.1269422 | GB | negative | contract | f | Bronze | 418.0 | 831581327
24854602977644353049269284436324 | Tullich | 57.4694803 | -3.1269422 | GB | negative | contract | f | Bronze | 418.0 | 831581327
In the next you will persist your query (also known as create table as select or CTAS) as a new dataset that you will use in Microsoft Power BI.
Next Step: 5.1.5 Generate a dataset from a query
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