12. If no one trusts your data, it’s essentially useless.
Everyone can access the same quality data
Garbage in – Garbage out (GIGO)
Data catalogs act as guides
Data governance as part to being data-driven
15. Data Democrazitation
Make data available to the people
Access to data that can help business users
Users are finding ways to liberate that data on their own
16. Open point for Data Democrazitation
Unregulated access to data
Siloed projects put compatibility, compliance, and security at risk
Who owns data and what its intended purpose is
17. „Every employee should be empowered to make data informed
decisions.“
„In order to inform every decision with data, it wouldn’t be possible to
have a data scientist in every room — we needed to scale our skillset.“
28. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context
30. Being data-informed, not data-driven
-12% engagement (time spent in product) and neutral conversion
+22% conversion, with engagement staying neutral
„We weren’t binary, we didn’t throw it away completely at the first sign
of trouble.“
Alastair Simpson
31. „Data and A/B test are valuable allies, and they help us understand and
grow and optimize, but they’re not a replacement for clear-headed,
strong decision-making.“
„Don’t become dependent on their allure. Sometimes, a little instinct
goes a long way.“
Julie Zhuo
Facebook Product Director
32. Context-driven visualization
Not everything that can be counted counts, not everything that counts
can be counted.
Qlik DataMarket as integrated DaaS (data as-a-service) offering
So you used the data to inform you, but ultimately the deciding factor
was you.
33. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
34. Analytics is about impact
No change -> zero credit
Tie actions to outcome
Distill it down to actionable insights.
These insights should drive real-time decision
35. Ensure that insights lead to action
1. How will data visualizations be distributed?
2. Do you have the right people available who can review the data?
3. What existing KPIs and measures will be disrupted?
4. Who is likely to support this change?
5. Who is likely to resist it?
36. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture
37. Definition of culture
„The way we do things around here.“
„How data is used to organize activities, make decisions and resolve
conflict.“
38. „Data-driven companies establish processes and operations to make it
easy for employees to acquire the required information, but are also
transparent about data access restrictions and governance methods.“
39. Infonomics
How do you measure the value of information?
Treating data as an enterprise asset in everyday practice.
Information's value in terms of its realized value and potential value.
40. Ability to confront the brutal facts
If the data tells you bad news
The human, financial and reputational impacts can be devastating
41. Data-driven culture
Lives and dies by example behavior
Executives are looking for the right data to base decisions on
Communication about how data-driven their decision making has been
43. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture Interpretation
46. How to start? Simply step back and ask.
1. What does this mean for the business?
2. Can I even trust these numbers?
3. Does this mean what I think it means?
4. What tracking should be in place?
5. Is this data usable and accessible by the teams?
47. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture Interpretation Data Integrity
48. Data integrity
„Data integrity can be described as the accuracy and consistency of
data throughout its entire lifecycle of being used by business or
technical processes.“
Keith Furst
53. Compliance risk in ETL process
Was all of the data extracted properly?
Was all of the data transformed from the source to the target system
as designed?
Was all of the data loaded from the source to the target system
successfully?
54. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture Interpretation Data Integrity
55. Take the time to ask critical questions
Being good at analytics is about asking good questions.
More data isn’t always a good thing; if it’s poor quality data, you may
just be more confident in making bad decisions.
Take the time to ask critical questions
56. Take away
Developing a fully optimized data-driven capability can be difficult and
costly, but getting started doesn't have to be.
Hackathon is the perfect chance to show off your #QlikSense skills –
and have fun too!
57. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture Interpretation Data Integrity
58. Data Driven Data Quality
Data
Democrazitation
Data Analysis Context Impact
Culture Interpretation Data Integrity