Bringing Big Analytics to the Masses Neal Leavitt

Transcription

1 Bringing Big Analytics to the Masses Neal Leavitt CS846 short paper presentation Song Wang /9/29

2 Motivation Agenda Issues for Small Business Analytics for all Drawbacks Summary /9/29

3 Motivation Big data analytics is valuable to many big companies 90% of Fortune 500 companies have big data analytics Google, Facebook, Amazon etc. sales, marketing, customer support /9/29

4 Motivation Big data analytics is valuable to many big companies 90% of Fortune 500 companies have big data analytics Google, Facebook, Amazon etc. sales, marketing, customer support Small businesses also can be benefited from big data analytics data volumes growing 62% annually big data analytics could dig out useful information /9/29

5 Motivation Big data analytics is valuable to many big companies 90% of Fortune 500 companies have big data analytics Google, Facebook, Amazon etc. sales, marketing, customer support Small businesses also can be benefited from big data analytics data volumes growing 62% annually big data analytics could dig out useful information Big data is too complex and expensive complex: efficient mining algorithms, auto-system expensive: data collection, storage, processing /9/29

6 Issues for Small Business Big data analytics requirements /9/29

7 Issues for Small Business Big data analytics requirements skilled IT staff (higher salaries) /9/29

8 Issues for Small Business Big data analytics requirements skilled IT staff (higher salaries) serves (expensive) /9/29

9 Issues for Small Business Big data analytics requirements skilled IT staff (higher salaries) serves (expensive) complex software (specialized programming languages, advanced tech) /9/29

10 Issues for Small Business Big data analytics requirements skilled IT staff (higher salaries) serves (expensive) complex software (specialized programming languages, advanced tech) Data is heterogeneous different types, sources structure and un-structure data /9/29

11 Issues for Small Business Big data analytics requirements skilled IT staff (higher salaries) serves (expensive) complex software (specialized programming languages, advanced tech) Data is heterogeneous different types, sources structure and un-structure data Technique issues complex and advanced technologies are needed technologies are changing rapidly /9/29

12 Issues for Small Business Big data analytics requirements skilled IT staff (higher salaries) serves (expensive) complex software (specialized programming languages, advanced tech) Data is heterogeneous different types, sources structure and un-structure data Technique issues complex and advanced technologies are needed technologies are changing rapidly Life is hard! /9/29

13 Issues for Small Business Big data analytics requirements skilled IT staff (higher salaries) serves (expensive) complex software (specialized programming languages, advanced tech) Data is heterogeneous different types, sources structure and un-structure data Technique issues complex and advanced technologies are needed technologies are changing rapidly Open source options Apace Hadoop, Spark storage, infrastructure, skilled programmers /9/29

14 Analytics for all Handling big data for small businesses is challenge expensive, complex build their own system is difficult /9/29

15 Analytics for all Handling big data for small businesses is challenge expensive, complex build their own system is difficult Big data Analytics options for small businesses software-based approaches cloud-based services /9/29

16 Analytics for all Handling big data for small businesses is challenge expensive, complex build their own system is difficult Big data Analytics options for small businesses software-based approaches integrated system offered by professional companies more affordable IBM, Oracle, SAP etc. cloud-based services /9/29

17 Analytics for all Handling big data for small businesses is challenge expensive, complex build their own system is difficult Big data Analytics options for small businesses software-based approaches integrated system offered by professional companies more affordable IBM, Oracle, SAP etc. cloud-based services delegate everything to cloud services scalable, relatively inexpensive Amazon, BigML, InsightsOne etc /9/29

18 Potential benefits Drawbacks target customers by capturing useful information about them identify marketing strategy predict the risk of products /9/29

19 Potential benefits Drawbacks target customers by capturing useful information about them identify marketing strategy predict the risk of products Big data analytics for small organizations faces several potential hurdles software and services are too expensive /9/29

20 Potential benefits Drawbacks target customers by capturing useful information about them identify marketing strategy predict the risk of products Big data analytics for small organizations faces several potential hurdles security issues /9/29

21 Potential benefits Drawbacks target customers by capturing useful information about them identify marketing strategy predict the risk of products Big data analytics for small organizations faces several potential hurdles does not see a business need for it /9/29

22 Summary Big data analytics is valuable to both big and small companies, big companies can build complex in-house machine-learning tools to conduct analytics, while it s challenge for small ones. Third-part software or cloud-based services could be helpful for small business to analyze data Providers could improve services figure out ways to make big analytics less complex, easier to use handle different domains /9/29

23 Thank you for your attention /9/29