1) The document discusses trends in big data and data-driven decision making. It notes that by 2017, 30% of enterprise access to big data will be through data broker services and by 2018 there will be a 35% shortfall of data-savvy workers. Using big data fully could increase retailer operating margins by 60%. 2) Common challenges for companies include integrating data from different sources, performing advanced analytics beyond basic reporting, and democratizing data access across all employee levels. 3) The document promotes a company called Keboola that helps connect different data sources to break down data silos and reduce the cost of infrastructure, while also providing ready-to-use advanced analytics applications.

1. Data driven in Social Media
1Pavel Bulowski - Partner - Keboola Singapore - @Pbulowski - pb@keboola.com

2. TRENDS THAT MATTER
30%
of enterprise access to
broadly based big data
will be via intermediary
data broker services,
serving context to
business decisions by
2017.
Gartner [2015]
2
35%
shortfall of data-savvy
workers needed to
make sense of out big
data by 2018
McKinsey [2011]
60%
we estimate, is by how
much an average
retailer using big data
to the full potential can
increase its operating
margin
McKinsey’s [2015]
Context Technology Efficiency

3. 1) Data integration – organisation struggling to bring all
their meaningful business data under one roof. Consolidation
typically takes up to 85% of their analytical capability.
2) Advanced analytics – companies cracked their basic
operational, ‘static’ reporting and are working on predictive
modeling, advanced segmentation, leveraging machine
learning and similarly evolved practices.
3) Data democratisation efforts – these companies truly
understand what being #datadriven means. They don’t
reserve insights for top level executive teams, but distribute
information vertically for all levels of employees to leverage
and create value.
DATA MATURITY
3

4. Connecting your data
We make it easy to connect all
data important to your
business by breaking the silos.
CHALLENGES WE SOLVE
2
Reducing cost of data
infrastructure
We remove the burden of
updating your home grown or
legacy ETL so you can focus on
your business.
4
1 3
Advanced Analytics
We bring you ready to deploy
data science applications to
get new value from your data
faster.

5. Client’s problems we solve
Marketing Manager
5
Data overload – dealing with many data sources and data types.
Consolidating everything for our final reporting takes full time resources.
Not enough time – campaigns start before we are finished evaluating
the last one, it’s time consuming
Offline vs. Online – how do we find the link?
Attribution – how do we allocate budgets?

6. Client’s problems we solve
Business Analyst / Data Scientist
6
Disjointed data - rather than developing new hypothesis we spend
time organising disjointed data.
Data hygiene - lots of time is being wasted on data quality issues,
fixing this never ends.
Iteration speed - preparing and implementing new algorithms is
ineffective and their iteration time consuming.

7. 7
Data driven in Social Media Marketing

8. Social data universe
8
Social Listening
Qualitative research
“media” monitoring (noise)
Crisis management
Benchmarking & Insights
Native and Free Insights
Competitive analysis
Social Customer Care
Lowering the cost of CS
New lead generation
Reputation Management
Publishing
Social CMS
Ads planning

9. “I believe that large amounts of data are being retained
because users have no way of identifying obsolete data; the
penalties for storing obsolete data are less apparent than are
the penalties for discarding potentially useful data.”
I.A. Tjomsland 1980

10. 10
Why visualisation doesn’t matter.

15. Why data integration matters.

17. Why all the way, one go must..

20. 20
Digging Deeper
From SILO To CONTEXT

21. 21

22. 22

23. 23
#Integrated

24. 24And this is why visualisation doesn’t matter. (that much)
Lead/conversion attributed to individual posts

25. But stop there one must not..
25

26. 26
● Custom content scoring algorithm
● Business potential prediction
● Advanced machine learning

27. 3 things I’d like you to leave with
Break the
silos
Connect
your data
27
Ask tough
questions
Show me
the
$$$

28. With Keboola, you can have all your data in one
place and distribute tailored insights to
stakeholders across your business.