Dashboards have become a standard business and operations tools. Unfortunately, many of them are overloaded and difficult in daily use. This presentation covers high-level know-how to build focused, thoughtful, and user-friendly dashboards. Namely it includes base principles and graphical design, explanation of practical usage of APEX components, Charts, JET-technology, and Plugins. Also the approaches to modify Oracle DB, using both well-known and newest 12C features, to get answer almost in real-time are described.

1. From Data to Knowledge © 2017 FRT Consulting1
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FRT Consulting GmbH
How to build the perfect dashboard
Pavel Glebov

2. From Data to Knowledge © 2017 FRT Consulting2
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• Spin off of Technical University/Graz, private held, MD: Gustav
Sperat
• HQ: Graz, Office Eastern Austria: Mödling
• 12+ people staff (internal, external), all experienced consultants,
currently upgrading to 15.
• Revenues: 2014, € 830 k, 2015, 880k, 2016 rd, 900k, no banking
loans, high percentage cash
• Main Business Focus:
• Enterprise Data Analytics
• Customers: Mostly Austrian Top100 in Telco, Manufacturing,
Finance and Services (see customer list)
• Network of partnerships with special expertise organizations
FRT Consulting – corporate profile
Facts, figures, strategy

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FRT Consulting – Analytics Portfolio
Consulting in DWH/BI architekture
Implementation specific platform, toolevaluation
KPI/reporting implementations
Systemintegration
Evaluation Usecases
Data preparation,visualisation
data exploration&analyse, modeling
Model execution, presentation
BigData
Data
ManagementDWH/BI
Data Governance
Data Quality
Data Security
Meta&Reference Data Mgmt.
Enterprise Data Analytics
Hybridkoncepts

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• Manufacturing:
• Andritz AG
• Prinzhorn Holding
• Elk Fertighaus
• SonyDADC
• Stora-Enso
• Telco / Utilities:
• Hutchison DREI Austria
• UPC
• E-Control
• Verbundgesellschaft
• KELAG
• Finance:
• Österr. Nationalbank - OeNB
• Merkur Versicherung
• Bonus Vorsorgekasse
• Heta Asset Resolution
• Basler Versicherung AG
• Services, HC, others
• Mazda Austria&SEE
• Tirol Kliniken
• Verbundlinien Stmk
• VBW
Customer List (Sample)

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Sample Dashboard

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Purposes: Marketing

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Purposes: Welcome

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Purposes: Motivation

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Purposes: Information

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Purposes: Exceptions Highlighting

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Who is the audience?
24% 18% 10% 20% 26%

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• Name the DB.
• What would you do if you see some
Information?
• What would you like to see?
• Group the information
Prioritize Information Blocks

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Brain’s capacity: 7 ± 2

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Main Chart Types

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Special chart types

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Exotic chart types
https://d3js.org/
Condegram Spiral Plot DependencyWheel

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Exotic chart types :3D

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Exotic chart types: successful solutions

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Chart Types in APEX
• Build-in JET-Charts
• Plugins - apex.world
• JET-Charts
• Separate JS libraries

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Long page loading time

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Data to show on the Dashboard
SELECT *
FROM FS_ANIMAL_FARMING
WHERE ICON = ‘COW’
AND STAT_YEAR =
TO_DATE(‘2007’,’YYYY’)
AND…..complex condition

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Large Indexes are not optimal
STAT_YEAR ICON
2007 COW
2007 PIG
2007 TURKEY
2008 COW
2008 PIG
2009 COW
2009 PIG
STAT_YEAR ICON COUNT
2007 COW 1.234.348
2007 PIG 3.565.678
2007 TURKEY 45.367.867
2008 COW 1.536.377
2008 PIG 45.665.675
2009 COW 1.637.381
2009 PIG 3.766.678
INDEX TABLE

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Function-Based Index
FUNCTION
IS_ANIMAL_DISPLAYED_ON_DB
(P_YEAR IN FS_ANIMAL_FARMING.STAT_YEAR%TYPE,
P_ICON IN FS_ANIMAL_FARMING.ICON%TYPE,
P_ID IN FS_ANIMAL_FARMING.ID%TYPE
)
RETURN FS_ANIMAL_FARMING.ID%TYPE
DETERMINISTIC
// returns id if given animal should be displayed
// on the dashboard
//
// and NULL if not.

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Small Indexes based on Function
ID
101001001
STAT_YEAR ICON COUNT
2007 COW 1.234.348
2007 PIG 3.565.678
2007 TURKEY 45.367.867
2008 COW 1.536.377
2008 PIG 45.665.675
2009 COW 1.637.381
2009 PIG 3.766.678
INDEX TABLE

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Optimized Query
SELECT *
FROM FS_ANIMAL_FARMING
WHERE IS_ANIMAL_DISPLAYED_ON_DB(
P_YEAR => STAT_YEAR,
P_ICON => ICON
P_ID => ID ) IS NOT NULL

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Sample Query with Aggregation
SELECT ICON,
STAT_YEAR,
SUM(SUMMARY) AS TOTAL
FROM FS_ANIMAL_FARMING
GROUP BY ICON,
STAT_YEAR

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Materialized View
CREATE MATERIALIZED VIEW
FS_ANIMAL_FARMING_MV
REFRESH FAST ON DEMAND
ENABLE QUERY REWRITE
ENABLE ON QUERY COMPUTATION
AS
SELECT ICON,
STAT_YEAR,
SUM(SUMMARY) AS TOTAL,
COUNT(SUMMARY),
COUNT(*)
FROM FS_ANIMAL_FARMING
GROUP BY ICON,
STAT_YEAR;

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Materialized Views speeds Queries
STAT_YEAR ICON TOTAL
2007 COW 1.234.348
2007 PIG 3.565.678
2007 TURKEY 45.367.867
2008 COW 1.536.377
2008 PIG 45.665.675
2009 COW 1.637.381
2009 PIG 3.766.678
MV_TABLE
SELECT ICON,
STAT_YEAR,
SUM(SUMMARY) AS TOTAL
FROM FS_ANIMAL_FARMING
GROUP BY ICON,
STAT_YEAR;

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STALE Materialized View
SQL> SELECT MVIEW_NAME,
STALENESS,
ON_QUERY_COMPUTATION
FROM USER_MVIEWS;
MVIEW_NAME STALENESS O
----------------------------------------- ---------------------------- ---
FS_ANIMAL_FARMING_MV NEEDS_COMPILE Y
DBMS_MVIEW

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Materialized Views speeds Queries
STAT_YEAR ICON TOTAL
2007 COW 1.234.348
2007 PIG 3.565.678
2007 TURKEY 45.367.867
2008 COW 1.536.377
2008 PIG 45.665.675
2009 COW 1.637.381
2009 PIG 3.766.678
MV_TABLE
SELECT ICON,
STAT_YEAR,
SUM(SUMMARY) AS TOTAL
FROM FS_ANIMAL_FARMING
GROUP BY ICON,
STAT_YEAR;
MV_LOGS
CHANGES

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Contacts
FRT Consulting GmbH
Liebenauer Hauptstrasse 2-6
A-8041 Graz
Fon: +43 316 71 12 12 - 0
Fax: +43 316 71 12 12 - 99
pavel.glebov@frt.at