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©2013 Lavastorm Analytics. All rights reserved. 1
Survey Results
Analytics 2013
©2013 Lavastorm Analytics. All rights reserved. 2
Key findings from Lavastorm Analytics’ survey of
more than 600 business analysts, technologists,
data analytics professionals, managers, and C-
level professionals
©2013 Lavastorm Analytics. All rights reserved. 3
Who Completed the Survey?
©2013 Lavastorm Analytics. All rights reserved. 4
©2013 Lavastorm Analytics. All rights reserved. 5
©2013 Lavastorm Analytics. All rights reserved. 6
©2013 Lavastorm Analytics. All rights reserved. 7
Key Findings
©2013 Lavastorm Analytics. All rights reserved. 8
©2013 Lavastorm Analytics. All rights reserved. 9
In which areas will you be
investing more resources?
©2013 Lavastorm Analytics. All rights reserved. 10
In What Area is Your Company Investing in 2013?
CONCLUSION:
Predictive analytics
and Big Data are
driving investment
©2013 Lavastorm Analytics. All rights reserved. 11
What is Your Biggest Challenge in Analytics Today?
QUOTABLE “…understanding what it takes to action findings! Findings
that cannot be acted on are often just “interesting”.”
©2013 Lavastorm Analytics. All rights reserved. 12
What Self-service Analytic Tool are You Currently Using?
CONCLUSION:
Tools for analysis
are fragmented;
People are still
relying on basic
spreadsheets
and databases,
not really
designed for
analytics
©2013 Lavastorm Analytics. All rights reserved. 13
QUOTABLE
“…shortage of true
data scientists
capable of
marrying big data
skills with business
acumen…”
©2013 Lavastorm Analytics. All rights reserved. 14
Conclusions – What You are Facing
Bandwidth/Skills Data Explosion
Need for Speed
©2013 Lavastorm Analytics. All rights reserved. 15
About Lavastorm Analytics
©2013 Lavastorm Analytics. All rights reserved. 16
Lavastorm Solves Your Analytic Challenges
Analytic Challenges Lavastorm’s Difference
Skills  Gives analysts the power of programmers for analytics
 High-level, visual building blocks capture analytic logic
 Visualizations and visual models help analysts present results
Data Integration  Acquire virtually any source data – no overarching schema
 “Precise” control to profile, inspect, transform
 Automates processes, including data quality
Agility  10x acceleration of integration and analytic projects
 Design, test, debug, and deploy in one place
Trust  Visual models expose analytic logic, create audit trail,
building trust with managers/peers
ROI  Empowers users for insight discovery, decision
making, process automation
 Start small – single toolset goes from desktop to data center
©2013 Lavastorm Analytics. All rights reserved. 17
Questions, Next Steps
Get Lavastorm Analytics Engine Public Edition (FREE)
http://www.lavastorm.com/resources/software-downloads-trials/
Follow Us
www.lavastorm.com
Lavastorm_News
Lavastorm Analytics Group
Lavastorm Analytics

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Analytics 2013 Survey Results Lavastorm Analytics

  • 1. ©2013 Lavastorm Analytics. All rights reserved. 1 Survey Results Analytics 2013
  • 2. ©2013 Lavastorm Analytics. All rights reserved. 2 Key findings from Lavastorm Analytics’ survey of more than 600 business analysts, technologists, data analytics professionals, managers, and C- level professionals
  • 3. ©2013 Lavastorm Analytics. All rights reserved. 3 Who Completed the Survey?
  • 4. ©2013 Lavastorm Analytics. All rights reserved. 4
  • 5. ©2013 Lavastorm Analytics. All rights reserved. 5
  • 6. ©2013 Lavastorm Analytics. All rights reserved. 6
  • 7. ©2013 Lavastorm Analytics. All rights reserved. 7 Key Findings
  • 8. ©2013 Lavastorm Analytics. All rights reserved. 8
  • 9. ©2013 Lavastorm Analytics. All rights reserved. 9 In which areas will you be investing more resources?
  • 10. ©2013 Lavastorm Analytics. All rights reserved. 10 In What Area is Your Company Investing in 2013? CONCLUSION: Predictive analytics and Big Data are driving investment
  • 11. ©2013 Lavastorm Analytics. All rights reserved. 11 What is Your Biggest Challenge in Analytics Today? QUOTABLE “…understanding what it takes to action findings! Findings that cannot be acted on are often just “interesting”.”
  • 12. ©2013 Lavastorm Analytics. All rights reserved. 12 What Self-service Analytic Tool are You Currently Using? CONCLUSION: Tools for analysis are fragmented; People are still relying on basic spreadsheets and databases, not really designed for analytics
  • 13. ©2013 Lavastorm Analytics. All rights reserved. 13 QUOTABLE “…shortage of true data scientists capable of marrying big data skills with business acumen…”
  • 14. ©2013 Lavastorm Analytics. All rights reserved. 14 Conclusions – What You are Facing Bandwidth/Skills Data Explosion Need for Speed
  • 15. ©2013 Lavastorm Analytics. All rights reserved. 15 About Lavastorm Analytics
  • 16. ©2013 Lavastorm Analytics. All rights reserved. 16 Lavastorm Solves Your Analytic Challenges Analytic Challenges Lavastorm’s Difference Skills  Gives analysts the power of programmers for analytics  High-level, visual building blocks capture analytic logic  Visualizations and visual models help analysts present results Data Integration  Acquire virtually any source data – no overarching schema  “Precise” control to profile, inspect, transform  Automates processes, including data quality Agility  10x acceleration of integration and analytic projects  Design, test, debug, and deploy in one place Trust  Visual models expose analytic logic, create audit trail, building trust with managers/peers ROI  Empowers users for insight discovery, decision making, process automation  Start small – single toolset goes from desktop to data center
  • 17. ©2013 Lavastorm Analytics. All rights reserved. 17 Questions, Next Steps Get Lavastorm Analytics Engine Public Edition (FREE) http://www.lavastorm.com/resources/software-downloads-trials/ Follow Us www.lavastorm.com Lavastorm_News Lavastorm Analytics Group Lavastorm Analytics

Hinweis der Redaktion

  1. BANDWIDTH and SKILLS – More analytics are required, but scarce bandwidthDATA EXPLOSION – Analysis of more data and data typesNEED for SPEED – Faster ways to draw insights from the data, ability to explore data more freely
  2. Data integration and data quality: Building a new infrastructure Maintaining trustJoining it with traditional BISkills and analytic capabilitiesAnalyticalTechnicalPresentationROI, Getting Value from the Data