Big Data Investment Theme – Fidelity Investments
Fidelity Investments put out an interesting analysis on Big Data as a Macro Investment Themes for clients. Since everyone has an underperforming investment portfolio in this current market, I reproduced the article here to generate some ideas.
Key Takeaways
- New types of large data sets have emerged because of advances in technology, including mobile computing, and these data are being examined to generate new revenue streams.
- More traditional types of business data have also expanded exponentially, and companies increasingly want and need to analyze this information visually and in real time.
- Big data will be driven by providers of Internet media platforms, data amalgamation applications, and integrated business software and hardware systems.
Investment Theme – Big Data
The concept of “big data” generally refers to two concurrent developments. First, the pace of data accumulation has accelerated as a wider array of devices collect a variety of information about more activities: website clicks, online transactions, social media posts, and even high-definition surveillance videos.
A key driver of this flood of information has been the proliferation of mobile computing devices, such as smartphones and tablets. Mobile data alone are expected to grow at a cumulative annualized rate of 92% between 2010 and 2015 (see Exhibit 1, below). Read more 
Predictive Analytics – A Project or a Program?
Our AMEX credit card was recently compromised. Someone got hold of the card information and Petro Canada charges started to rack up. Amex spotted this suspicious pattern and immediately initiated a fraud alert thru multiple touch points.
What does your credit card company know about you? A lot…maybe more than your spouse. A study of how customers of Canadian Tire were using the company’s credit cards found that 2200 of 100,000 cardholders who used their card at drinking places missed four payments within the next 12 months. By contrast, only 530 of the cardholders who used their card at the dentist missed four payments within the next 12 months. So drinking is a predictor of credit risk.
Predictive analytics is not a fad. It’s not a trend. In a real-time world, Analytics is a core business requirement/capability. However, many organizations flounder in their efforts not because they lack analytics capability but because they lack clear objectives. So the first question is, What do you want to achieve?
Analytics so far has largely been a departmental ad hoc activity. Even at the most sophisticated corporations, data analytics is a cumbersome affair. Information accumulates in “data warehouses,” and if a user had a question about some trend, they request “data priests/analysts” to tease the answers out of their costly, fragile systems. This resulted in a situation where the analytics are done looking in the rearview mirror, hypothesis testing to find out what happened six months ago.
Today it’s possible to gather huge volumes of data and analyze it in near real-time speed. A retailer such as Macy’s that once pored over last season’s sales information could shift to looking instantly at how an e-mail coupon impacts sales in different regions. Moving to a realtime model and also building an enterprise level “shared services” model is going to be the next big wave of activity.
Read more
Big Data Infographic and Gartner 2012 Top 10 Strategic Tech Trends
Data, data and more data…data is everywhere…data is important… By 2015, nearly 3 billion people will be online, pushing the data created and shared to nearly 8 zettabytes. Centurylink created this cool infographic to highlight the data deluge and big data issues. Gartner 2012 Top 10 Tech Trends illustrated some examples of this.
- 30 billion pieces of content were added to Facebook this past month by 600 million plus users.
- Zynga processes 1 petabyte of content for players every day, a volume of data that is unmatched in the social game industry.
- More than 2 billion videos were watched on YouTube … yesterday.
- The average teenager sends 4,762 text messages per month.
- 32 billion searches were performed last month … on Twitter.
- Worldwide IP traffic will quadruple by 2015 (Cloud is a big driver for this; most corporations are racing to upgrade networks and connectivity)
Time for a strategy…. I have visited several large corporations in the past month that are beginning to build strategies and tangible plans. This may be the difference between reacting and prospering in the world of Big Data and predictive analytics. Read more
What is a “Hadoop”? Explaining Big Data to the C-Suite
Keep hearing about Big Data and Hadoop? Having a hard time explaining what is behind the curtain?
The term “big data” comes from computational sciences to describe scenarios where the volume of the data outstrips the tools to store it or process it.
Three reasons why we are generating data faster than ever: (1) Processes are increasingly automated; (2) Systems are increasingly interconnected; (3) People are increasingly “living” online.
As huge data sets invaded the corporate world there are new tools to help process big data. Corporations have to run analysis on massive data sets to separate the signal from the noisy data. Hadoop is an emerging framework for Web 2.0 and enterprise businesses who are dealing with data deluge challenges – store, process, index, and analyze large amounts of data as part of their business requirements.
So what’s the big deal? The first phase of e-commerce was primarily about cost and enabling transactions. So everyone got really good at this. Then we saw differentiation around convenience… fulfillment excellence (e.g., Amazon Prime) , or relevant recommendations (if you bought this and then you may like this – next best offer).
Then the game shifted as new data mashups became possible based on… seeing who is talking to who in your social network, seeing who you are transacting with via credit-card data, looking at what you are visiting via clickstreams, influenced by ad clickthru, ability to leverage where you are standing via mobile GPS location data and so on.
The differentiation is shifting to turning volumes of data into useful insights to sell more effectively. For instance, E-bay apparently has 9 petabytes of data in their Hadoop and Teradata cluster. With 97 million active buyers and sellers they have 2 Billion page view and 75 billion database calls each day. E-bay like others is racing to put in the analytics infrastructure to (1) collect real-time data; (2) process data as it flows; (3) explore and visualize. Read more
IBM CIO Study: BI and Analytics are #1 Priority for 2012/2013
“Running a company is an endless quest to find out things you don’t know“
– Jeff Immelt, CEO GE
What will 2012 bring? Recently, I attended the CIO Executive Leadership Summit in Greenwich, Connecticut. I was particularly intrigued by the presentation by the new CIO of IBM, Jeanette Horan where she presented the projects she was tackling and how IBM is thinking about business analytics.
IBM is making a bet that “true leaders” will develop the capabilities required for making good and timely decisions in unpredictable and stressful environments.
IBM is adapting to this new data analytics reality by a rapid-fire acquisition strategy: Cognos, Netezza, SPSS, ILog, CoreMetrics, Algorithmics, OpenPages, Clarity Systems, Emptoris, DemandTec (for retail). IBM also has other information management assets like Watson, DB2 etc. They are building a formidable capability around the value chain: “Raw Data -> Aggregate Data -> Intelligence ->Insight -> Decisions” . They see this as a $20Bln opportunity. Read more
Oracle’s Analytics-as-a-Service Strategy: Exalytics, Exalogic and Exadata
Following the success of its Exadata (database as a service) and Exalogic (middleware-as-a-service) engineered systems, Oracle unveiled Exalytics Business Intelligence at Oracle OpenWorld 2011.
The goal of these appliances (engineered systems) is to help IT groups further shrink data center costs, increase system utilization and enable better application integration. All goals that CIOs everywhere continue to struggle with. CIOs now face an interesting decision matrix: Exalytics/Logic/Data systems versus traditional build from components versus hosted.
With ExaSystems, Oracle has a tremendous market advantage. Oracle owns most of the software that enterprises need today. Via acquisitions, Oracle owns the whole stack! Web tier, Middleware, Database software, Database tier, Storage tier. With Sun Microsystems it’s ideally positioned to maximize the platform capabilities. It’s easy for Oracle make its own software play nice on the Exalytics, Exalogic and Exadata platforms.
Wanted: CIO – BI/Analytics
In a tough economy, a new tech-fueled BI and analytics arms race is on to create the next competitive advantage.
Everyone is beginning to look beyond the status quo in BI, analytics, Big Data, Cloud Computing etc to fundamentally change how they discover fresh insights, how they can make smarter decisions, profit from customer intelligence and social media, and optimize performance management.
The headache for corporations is not the technology aspects but the leadership side. Who is going to lead this effort, corral the vendors and formalize and execute a more structured program.
Who is going to lead the effort to create the right toolset, dataset, skillset and mindset necessary for success?
As BI and Analytics moves from “experiment and test” lab projects to commercial deployments, companies are going to need more leadership and program management capabilities. They need leadership that can provide strategic, expert guidance for using powerful new technologies to find patterns and correlations in data transactions, event streams, and social media.
Some firms are making moves. In insurance, AIG – Chartis Inc. unit appointed Murli Buluswar to the new post of chief science officer. This aims to enhance Chartis’ focus on analytics… he “will be responsible for establishing a world-class R&D function to help improve Chartis’ global commercial and consumer business strategies and to deliver more value for customers.” This focus on analytics involves “asking the right questions and making science-driven decisions about strategies—whether it’s related to underwriting decisions, product innovation, pricing, distribution, marketing, claims or customer experience—with the end result of improving the scope of what Chartis delivers for customers”.
As a result of where we are in the maturity cycle and to support the business units better, we are seeing a new emerging role “CIO – BI” that is dotted lined to the global CIO or a shared services leader. Let’s look at a representative job posting from GE Capital, which always seems to be a step ahead of most companies. Read more
Sentiment Analytics, Twitter, Federal Reserve and Consumer Pyschology
What do these have in common: The Federal Reserve Bank, Text Analytics, Facebook, Statistical Computations, Big Data and Keyword/Phrase/Boolean searching?
Interestingly these are more related than you think.
The Federal Reserve wants to develop a next generation Consumer Listening Platform based on social media sentiment analytics (or opinion mining) to know what people are saying and commenting about the economy.
The goal for the Fed is to better understand which way consumer confidence is trending. Microeconomics and psychology have always been interlinked. With social media, a real-time opportunity exists to monitor local, national and even global consumer psychology. And, coupled with analyzing e-commerce transactions, insightful linkage between consumer psychology and behavior (what they are spending money on and where) is possible. Read more
Do you have BI Performance Anxiety ?
BI is key to enabling companies to turn oceans of data into predictive models and actionable decisions. However, a survey of 353 executives in large companies, reported that their chief BI concern was the performance of various BI solutions.
Development, support and enhancement teams are typically deployed to address BI performance challenges with varied success. But most companies don’t have a dedicated focus on performance.
A BI Center of Excellence (BI CoE) measured by performance KPIs and service metrics is one solution to this problem. This is not an area that traditionally draws high-level attention or is featured in a dedicated CoE initiative, yet in the right circumstances it offers unique value. Read more
Is Your BI Project in Trouble?
Enterprise Business Intelligence (BI) project failure can happen for a variety of reasons. Sometimes it’s due to frequent scope changes with a fixed schedule constraint, unexpected and unplanned-for “must-have” requirements changes, loss of key team members onshore or offshore, chronic effort under-estimation, lack of proper work breakdown structure, lack of QA, and so on.
Regardless of the causes, BI, Analytics, performance management failed projects waste billions of dollars (and hours) each year.
Over the years, I have seen a lot of well-intentioned custom development, commercial, off-the-shelf package customization – SAP, Oracle, Peoplesoft ERP, CRM, SCM – and other enterprise data-warehouse projects get into trouble for a variety of reasons. Troubled projects usually need triage, recovery, and turn-around skills to straighten things out quickly.
I am afraid that BI and Corporate Performance Management is reaching a phase in its hype cycle where we are beginning to see growing demand for troubled project recovery. It doesn’t take genius to realize that BI/Analytics project demand is growing as it is one of few remaining IT initiatives that can make companies more competitive. However, demand doesn’t imply project success. Read more
Shirish Netke
Ravi Kalakota
Business Analytics 3.0 