How to identify the Return on Investment of Big Data / CIO

Editor's Notes

• #2: If you are a CIO, you know what goes on at a board of directors meeting. This is not the right place to be confused when the CEO is asking you this common and simple question, which requires a very simple and accurate answer: “What is the ROI of Big Data costs?”
• #3: Let’s be honest, Big Data is a big, painful issue. It is recommended to use few information in your dashboard if you expect to be heard. But at the same time, you want this information to be true, right? That’s when you are happy that your data is big. ROI is all about results. Big Data is here to stay and bigger data is coming, so the best we can do is to make it worth the trouble.
• #4: Experts often say that Big Data doesn’t have much value simply stored; your spending on big data projects should be driven by business goals. So it’s not a surprise that there is increased interest in gaining insights from Big Data and making data-based decisions.
• #5: “Cloud is the new electricity,” according to the latest IT Industry Outlook published by CompTIA. But I don’t have good news for you, if you feel comfortable just planning to move your data to the cloud. This is just the beginning.
• #6: In fact advanced analytics and self-service reporting is what you should be planning for your big data. I’ll tell you briefly: Why you need to support democratization of data integration and data preparation in the cloud. Why you should enable software for self-service advanced and predictive analytics. Why Big Data insights and reporting should be put where they’re needed.
• #7: Data scientist spent around 80% of their time on preparing data, rather than actually getting insights from it – so interest in self-service data preparation is growing. Leaving the data cleansing to data scientist may be a good idea for some of their colleges but actually it is not a good idea in terms of agility and accuracy.
• #8: Gartner predicts that the next big market disruption is self-service data preparation, which by 2019 will represent 9.7% of the global revenue opportunity of the business intelligence market. So we will hear more about it in the near future.
• #9: Big data analytics, recruiting talent and user experience top the CIO agenda for 2016, according to The Wall Street Journal; but those gaps will be hardly solved at the same time, because of the shortage of data-savvy people. Actually according to Gartner there is an anticipated 100,000+ person analytic talent shortage through 2020.
• #10: Companies have been able to identify ROI of big data using predictive analytics to anticipate risk or forecast opportunities for years. For example, banks, mortgage lenders, and credit card companies use credit scoring to predict customers’ profitability. They have been doing it even when complex algorithms often require data scientists, hard-to-find expertise, not just to build but to keep running. That limits their spread throughout an organization. That’s why OpenText™ Big Data Analytics in the Cloud is including ad-hoc and pre-built algorithms like Profile, Forecast, Decision Tree or Association Rules
• #11: No doubt that all use cases are not created equal. According to Aldous Huxley “most people use statistics the way a drunkard uses a lamp post, more for support than illumination”. Very small businesses may find desktop tools like Excel good enough for their data analysis, but after the digital disruption those tools have become inadequate even for small Retail firms.
• #12: Embedded visualizations and self-service reporting are key to allow the benefits of data-driven decisions into more departments, because it doesn’t require expert intervention. Instead, non-technical users can spontaneously “crunch the numbers” on business issues as they come up. Actually 74% of marketers can’t measure and report on the contribution of their programs to the business according to VisionEdge Marketing.
• #13: You should always ensure that the security and scalable capabilities of the tool you need is carefully selected, because in such cases you will be dealing not only with billions of rows, but also maybe millions of end users.
• #14: Identification of the ROI of big data is pending on the democratization of the business insights coming from advanced and predictive analytics of that information like in their case. Nobody said it is simple but it can lower operating costs and boost profits, which every business users identifies as ROI. Moreover when line-of-business user rather than technology user are driving the analysis, and the right people are getting the right insight when they need it, improved future actions should feed the wheel of big data with the bigger data that is coming. And sure you want it to come to the right environment, right?
• #15: UPS gather information at every possible moment and already store over 16 petabytes of data. They make more than 16 million shipments to over 8.8 million customers globally, receive on average 39.5 million tracking requests from customers per day, employ 399.000 people in 220 different countries. They spend $1 billion a year on big data but their revenue in 2012 was $ 54.1 billion.
• #16: There is huge number of analytics tools which main goal is to solve the mentioned business problems but, which one is best for you? I will tell you why OpenText Analytics is best
• #17: OPENTEXT™ is the leader in Enterprise Information Management and its RELEASE 16 is the most complete, integrated digital information platform for the enterprise. ANALYTICS SUITE 16 is offered in the cloud, on-premises or in a hybrid environment. OPENTEXT™ BIG DATA ANALYTICS main value proposition is speed when processing large amount of data: The fastest analysis of big data from multiple data sources is possible because of its columnar database architecture. Data can be loaded by frontend or back-end and any user can be enabled to self-service data preparation, data cleansing and data audit. Self-service advanced segmentation and predictive analytics through ad-hoc tools and pre-build analysis. Easy to report, export, schedule tasks or run campaigns workflows – and of course, seamlessly integrated with OpenText™ Information Hub. OPENTEXT™ INFORMATION HUB main value proposition is personalization of embedded reporting: Design & Deploy HTML5 data visualizations and embedded business intelligence with easy drag-and-drop user interface. Secure personalization and scalability of information, reports and dashboards to any audience size. Easy to integrate into any application or device – quicly and seamlessly by leveraging OpenText’s Javascripts or REST APIs. Benchmark-proven scalability and performance to accelerate application time to market and improve user adoption.
• #18: But how OpenText Analytics actually works?
• #19: The best way to have visual insights of how OpenText Analytics works is through the video tutorials that you can find at Youtube for Big Data Analytics https://goo.gl/LK3g9C or Information Hub https://goo.gl/VDCwLL Additionally you can register for a OpenText 30-Day Free Trial of Big Data Analytics at http://goo.gl/1cA4nQ or Information Hub at http://goo.gl/94JG29 And finally you can also request a Custom Demo with your Own Data by OpenText at http://goo.gl/boIzQn
• #20: I hope it helped but please contact me if I can do anything more for you! Jose Fernandez @gooowest