Why watch?
Are you trapped in reporting hell?
Do you spend hours struggling to manually produce the reports management demands? Are you working with disparate islands of outdated data? And, after all that hard work, are the reports produced inaccurate and untrustworthy?
Watch this on-demand Webinar from SolveXia and Yellowfin – Data Sourcing Best Practices for Reporting – to discover how to build reliable supply chains of data in just 30-minutes. Learn how to quickly and easily go from source data to killer report – every time.
Only dependable and repeatable processes can produce quality data and reports. Ensure your reporting generates the business insights you need. Let SolveXia and Yellowfin show you how.
What will you learn?
Think the ability to deliver world-class, up-to-date and accurate reports that anyone can access, analyze and act on is important? Then this Webinar is a must.
Watch the on-demand version to learn how to:
•Create business critical reports on which you and your organization can rely
•Deliver sleek, sexy and intuitive charts, reports and dashboards to anyone, anywhere, anytime on any device
•Become the information Superhero you were meant to be!
The data that underpins any reporting system must be managed properly to make sure it’s clean, relevant and delivered in a timely manner to maximize the ability of enterprise BI solutions to produce actionable insights. Do you know how?
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
Data Sourcing Best Practices for Reporting (Webinar slides)
1. 10 Data Sourcing Best
Practices 27 of February
Webinar – Thursday
th
2014
2. Welcome
Introducing the
speakers…
Adem Turgut
Lead Business
Analyst
SolveXia
Cameron Deed
Senior Consultant
Yellowfin
Agenda for this webinar:
Why is data quality
important?
Our 10 best
practices
Demonstration –
From data to
visualisation
Q&A
3. “Simplified our business…”
Nick Sutherland, Cofounder of CT Connections
Corporate Travel
Management
Online
Reporting
& Analytics
“Productivity gains that are
both dramatic but
continuous and
incremental”
Darren Robinson, Actuary
at Clearview Insurance
Process
Automation
Data
Warehousing
4. If you are looking for a user-friendly tool
with collaborative and mobile capabilities
that I refer to as the next generation of BI
software, take a look at Yellowfin
David Menninger
VP & Research Director
Ventana Research
6. Your data has reach…
Where data from a report is used:
Utilised by:
Within
department
31%
Inter-departmental
69%
CEO
42%
* Panko and Port, 2012
7. Just how much of an issue is data
quality?
1 in 10 organisations rate their data
quality as “excellent”
Poor data quality accounts for
20% of business process costs
$611bn
The cost of poor data quality to US
Companies each year
* Gartner, TDWI
8. And we want more…
x44 by 2020
2009 – enough data to fill a stack of
DVDs to the moon and back
2020 – Grow by 44x
Less than 1% of available data
is analysed
1%
93% of execs believe they are losing
revenue as a result of not fully
leveraging the information they collect
* IDC, Oracle and EMC
9. What is data quality?
HOW
TRUSTED
RELIABLE
AND
IS YOUR
CREDIBLE
DATA?
Complete
Accurate
Available
Consiste
nt
10. Why is data quality important?
“It can increase customer
satisfaction”
“It improves the success rate of enterprise
initiatives like Business Intelligence…”
“It supports accountability”
“It ensures the best use of our resources”
“It reduces the cost of rework”
“It increases our efficiency”
“It ensures we have the best possible
understanding of our customers and employees”
“It gives us accurate and timely
information to manage our business”
11. Building high quality “supply chains” of
data
GET THE
RIGHT DATA
MEASURE
FOR QUALITY
BE AGILE
12. 1 Focus on the outcome
ISSUES
Analysis Paralysis
Letting data dictate what is
“important”
Limited time and energy
to focus
14. 2 Profile your data
ISSUES
Data supplier doesn’t know
your data needs
The data you source is as
good as ….
15. RECOMMENDATIONS
2 Profile your data
Write your data profile
Structure, Format, Frequency, Age, Delivery Method
Communicate it to data providers
Identify issues and gaps
16. 3 Get as close to the source as possible
ISSUES
When your source data is somebody else’s
spreadsheet….
Availability of data
Human Error
Risk
Unexpected
Changes
Additional effort and complexity
17. RECOMMENDATIONS
3 Get as close to the source as possible
PLAN
CAUTION
Be cautious of
manual
spreadsheets
Skip the
spreadsheet as a
source
Communicate and
measure for quality
18. EXAMPLE
3 Get as close to the source as possible
Insurance Intermediary
Insurance Broker
Monthly CFO Report
Data sourced from manual
spreadsheet
Time consuming and risky
Monthly CFO Report
19. 4 Streamline data sources
ISSUES
Using multiple sources
Redundant data
Increased complexity and quality risk
20. 4 Streamline data sources
EXAMPLE
Identify redundant data
Focus on the essentials
Cut out the stuff you don’t need
21. ISSUES
5 Set data quality expectations
Perfectionism Burnout
Focusing on things that few care about..
22. RECOMMENDATIONS
5 Set data quality expectations
Focus on high impact data
RELAX
(a little)
Tolerances and ranges for quality and accuracy
23. 6 Catch data quality issues early
1-10-100 Rule:
If found at the start
of journey
Early
ISSUES
$1
If found in the middle
of the journey
$10
Late
If found at the end of
the journey
$100
* Total Quality Management
24. RECOMMENDATIONS
6 Catch data quality issues early
Implement quality measures near the start
of the data supply chain
Use the “start” as a reference point when
checking data further down the journey
25. EXAMPLE
6 Catch data quality issues early
Australian Life Insurer
New Business Reporting
26. ISSUES
7 Actively measure quality
Invalid Assumption:
If the data meets our expectations today, it
will going forward
No simple way to identify if data is correct
What happens when we do find an issue?
27. RECOMMENDATIONS
7 Actively measure quality
NOT GOOD
OK
GOOD
Define metrics for your data quality
Measure for quality on a consistent basis
Address consistent issues with strategic
solutions (e.g. data cleansing)
29. 8 Expect Change. Embrace It.
ISSUES
We all know change is coming
Business activity, changes in
strategies and systems.
So rigid that you need to
“reset”
30. Score and rank potential changes
H
Likelihood
RECOMMENDATIONS
8 Expect Change. Embrace It.
Focus on high likelihood/impact
changes
L
L
H
Impact
Have a plan in place for high risk
items
31. 9 Plan for change
ISSUES
A change occurs, then what?
Lack of clear policies and rules on who
needs to do what…
Knowledge resting in the minds of key
individuals
32. RECOMMENDATIONS
9 Plan for change
CAUTION
In the event
of a change
the following
people will…
Policies and rules
Documentation
Tracking
Changes