Making Predictive Analytics More Accessible to Business Analysts - Alteryx & Ventana Research Webinar

  • 1,427 views
Uploaded on

Ventana Research & Alteryx cover research findings on best practices and recommendations for predictive analytics. In addition they discuss the current analytic challenges organizations face and …

Ventana Research & Alteryx cover research findings on best practices and recommendations for predictive analytics. In addition they discuss the current analytic challenges organizations face and where predictive analytics provide the most benefit and how Alteryx is making ppredictive analytics more accessible to business analysts.

Learn more at www.alteryx.com

More in: Technology , Business
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
No Downloads

Views

Total Views
1,427
On Slideshare
0
From Embeds
0
Number of Embeds
3

Actions

Shares
Downloads
63
Comments
0
Likes
2

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. Making Predictive Analytics More Accessible to Business Analysts Matt Madden- Alteryx Tony Cosentino- Ventana Research © 2013 Alteryx, Inc. Confidential. 1
  • 2. Predictive Analytics Tony Cosentino VP & Research Director, Ventana Research Tony is responsible for the business analytics research practice including business intelligence, location intelligence operational intelligence, and predictive analytics. Tony is responsible for researching analytics, big data, cloud computing, business collaboration, mobile technology and social media. Tony is an accomplished author with his book titled Into the River: How Big Data, the Long Tail and Situated Cognition are the Changing the World of Market Insights Forever. His work has been published in Business 2.0, Marketing News, Information Management, SmartDataCollective, and many other publications. You can find Tony on Twitter at @tonycosentinovr, via email at tony.cosentino@ventanaresesarch.com or via his blog at http://tonycosentino.ventanaresearch.com. 1 © 2013 Ventana Research
  • 3. Predictive Analytics Predictive Analytics Insights from Benchmark Research Webinar Presentation Tony Cosentino VP & Research Director, Business Analytics 2 © 2013 Ventana Research
  • 4. Predictive Analytics What is Predictive Analytics? 3 3 © 2013 Ventana Research
  • 5. Predictive Analytics The Ethos of Big Data Analytics 4 • Moving from 20th to 21st century analytics: designed data and organic data • Moving beyond internal and external data silos • Moving beyond analytical silos • Moving from the V’s to the W’s © 2013 Ventana Research
  • 6. Four Pillars of Big Data Analytics • Intersection of BDA and traditional analytics: Predictive Analytics bringing structured and unstructured data together • Visual and data discovery: exploring data in many ways • Predictive analytics: reducing complexity and broadening scope • Real-time and right-time analytics: operationalizing analytics on an industrial scale 5 © 2013 Ventana Research
  • 7. Enabling the Five Analytic Personas A big data foundation must meet the following roles & responsibilities: Information Consumers Predictive Analytics • Digest information and perform basic interactions Knowledge Workers • Utilize and interact analytics to drive actions and decisions. Designers • Enable the design and use of information across roles. Analysts • Mash-up data and design analytics to provide foundational insights for business. Data Geek • Enable big data to be exploited in an immature world through Data Scientists. 6 © 2013 Ventana Research
  • 8. Predictive Analytics 7 7 © 2013 Ventana Research
  • 9. Key Insights into Predictive Analytics Predictive Analytics •Predictive analytics is very important to organizations •Predictive analytics maturity varies widely among organizations and people. •Revenue-generating functions are primary users of predictive analytics. •Various teams handle implementation of predictive analytics. Source: Ventana Research Predictive Analytics Benchmark Research 8 © 2013 Ventana Research
  • 10. Key Insights into Predictive Analytics Predictive Analytics •More timely results, and more frequently updated models are needed. •Inadequate resources and training for predictive analytics projects. •Line of business is funding predictive analytics projects. •Organizations expect further predictive analytics to have a positive impact. Source: Ventana Research Predictive Analytics Benchmark Research 9 © 2013 Ventana Research
  • 11. Predictive Analytics Opportunities 10 10 © 2013 Ventana Research
  • 12. Areas of Opportunity Marketing Analytics Predictive Analytics Human Capital Analytics 11 Operational Analytics Risk and Compliance © 2013 Ventana Research
  • 13. Top Five Benefits of Predictive Analytics Related Research Points: How has your benefited from predictive analytics: 68% Predictive Analytics Achieve competitive advantage 55% New revenue opportunities 52% Increased profitability Increased customer service Operational efficiencies • Management (76%) has no doubts that predictive analytics is a top priority. • Almost two thirds (65%) of marketing use today and another fifth (19%) by end of 2015. 45% 44% Key benefits of represent achievement in the process and using technology. Source: Ventana Research Predictive Analytics Benchmark Research 12 © 2013 Ventana Research
  • 14. Predictive Analytics Barriers 14 14 © 2013 Ventana Research
  • 15. Foundational Information Challenges Predictive Analytics Top five barriers facing organizations today Multiple versions of the truth 64% Data not timely enough 60% Data spread across too many apps and systems 67% Data not clean enough to use 58% Technology not able to meet needs 57% Source: Ventana Research Information Management Benchmark Research 15 © 2013 Ventana Research
  • 16. Technical Challenges in Predictive Analytics What technical challenges have been encountered in its use of predictive analytics: Predictive Analytics Difficult integrating into our information architecture Cannot access the necessary source data Results not accurate No challenges Too hard to use 22% 20% 35% 55% Related Research Points: • Midsize (73%) and Very Large (65%) businesses especially have difficulty integrating predictive analytics into their information architecture. • Largest barrier to making changes to predictive analytics technology is lack of resources (59%). 18% Source: Ventana Research Predictive Analytics Benchmark Research 16 © 2013 Ventana Research
  • 17. Changing Needs of Buyers Category % selecting Very Important 70% Capability 60% Reliability 58% Adaptability 47% TCO/ROI Manageability 33% Validation 26% Source: Ventana Research Technology Innovation Benchmark Research 17 • Small companies (83%) consider usability to be a very important consideration. • Functionality becomes relatively more important as company size increases 47% Predictive Analytics Usability Related research: © 2013 Ventana Research User experience and simplicity is most critical.
  • 18. Predictive Analytics 18 18 © 2013 Ventana Research
  • 19. What To Do Next Think broadly to educate and specifically to implement (e.g. The V’s, the W’s, 4 Pillars of BDA, Time-to-Value) 1 3 Predictive Analytics 2 4 19 Determine use case and best practices; address big data and revenue generating functions Evaluate the maturity of your organization with respect to People, Process, Information and Technology Create a cross-functional plan to specifically address skillsets and deployment process and tools © 2013 Ventana Research
  • 20. What To Do Next In starting out, find resources for deployment and raise awareness about the value of them. Predictive Analytics 5 6 7 20 Identify other tools and applications with which predictive analytics should be integrated Move to more granular models, right-time models, updated models © 2013 Ventana Research
  • 21. Predictive Analytics Predictive Analytics Insights from Benchmark Research Webinar Presentation Tony Cosentino VP & Research Director, Business Analytics 21 © 2013 Ventana Research
  • 22. Perception of the Immovable Object Between Big Data, Customer Analytics, and Business Value LEGACY BI PLATFORM DELIVERS SLOW INNOVATION & FAIL THE HARD QUESTION TEST CODING REMAINS A REQUIRED SKILL FOR ANALYTICS, WHILE DATA PROCESSING JUST TAKES TOO LONG CUSTOMER INSIGHT IS FOUND IN MORE PLACES THAN EVER THAT ARE NOT ACCESSIBLE TO THE BUSINESS ANALYST LONG, MULTI-USER IT ONLY PROCESSES SLOW INNOVATION AND ABILITY TO RESPOND © 2013 Alteryx, Inc. Confidential. 2
  • 23. Alteryx’s Mission is To Humanize Big Data and Empower Data Artisans Capabilities of Data Scientist that Drive Largest Value Today Line of Business Data or Business Analyst © 2013 Alteryx, Inc. Data Artisan 3
  • 24. Alteryx Empowers the Business Analyst Answering the important questions faster & simpler Fastest data blending in the hands of the business analyst © 2013 Alteryx, Inc. Confidential. Sophisticated analytics that are easier to use: no coding required Automatically share the insight and foresight of analytics with decision makers 4
  • 25. The Alteryx Solution For Analyst Enablement Blend, Analyze, Share Packaged Market & Customer Data All Relevant Data Enrich © 2013 Alteryx, Inc. Confidential. Share Analyze Blend Utilize & Integrate any data source Rapid design of predictive analytics with unique spatial understanding Consumerize the use of sophisticated analytics 5
  • 26. Alteryx Empowers the Business Analyst Answering the important questions faster & simpler Fastest data blending in the hands of the business analyst © 2013 Alteryx, Inc. Confidential. Sophisticated analytics that are easier to use: no coding required Automatically share the insight and foresight of analytics with decision makers 6
  • 27. Making Predictive Analytics Accessible To the Data Artisan By Bridging the Data Scientist Skills Gap 30+ prepackaged R tools to make predictive analytics accessible in any analytic workflow Programmers can write their own script or incorporate other R script into the workflow © 2012 Alteryx, Inc. Confidential. 7
  • 28. Predictive Analytics across the Cycle Missing Data Binning Data Impute Values Preparation Multi-Field Binning Data Understanding Investigation Spearman Correlation Coefficient Plot of Means Create Samples Frequency Table Oversample Field Pearson Correlation Coefficient Scatterplot Data Descriptions Field Summary Report Histogram Contingency Table Associations Grouping K-Centroids Analysis Association Analysis Append Clusters K-Nearest Neighbor Principal Components K-Centroids Diagnostics Future outcomes over time TS Plot TS ETS TS ARIMA Clustering Forecasting TS Compare TS Forecast Prediction AB Test Analysis AB Controls © 2013 Alteryx, Inc. Confidential. AB Treatments AB Trends Scoring Modeling Testing Forest Model Decision Tree Market Basket Rules Market Basket Inspect Count Regression Lift Chart Nested Tests Linear Regression Logistic Regression Stepwise Score Test of Means 8
  • 29. Demonstration © 2013 Alteryx, Inc. Confidential. 9
  • 30. Try it yourself.. Download Alteryx Project Edition today to begin creating your own analysis www.alteryx.com/download © 2013 Alteryx, Inc. Confidential. 10
  • 31. Inspire 2014 │Analytic Freedom Learn more: http://www.alteryx.com/inspire-2014-home Follow Alteryx on Twitter! @Alteryx #Inspire14 “This reminds me of our conference – similar audience passion for analytics and for the product & company.” Stephen McDaniel, Tableau © 2013 Alteryx, Inc. Confidential. 11