Myles Suer

Myles Suer
Mr. Suer is a senior manager of solutions marketing at Informatica Corporation. Much of Mr. Suer’s experience has been as a BI practitioner. At HP and Peregrine, Mr. Suer led the product management team applying BI and Scorecard technology to these company’s IT management products. Prior to HP, Mr. Suer led new product initiatives at start-ups and large companies. This included doing a restart of a Business Activity Monitoring Company. Mr. Suer has, also, been a software industry analyst. Mr. Suer holds a Master of Science degree from UC Irvine and a 2nd Masters in Business Administration in Strategic Planning from the University of Southern California.

Is Big Data Destined To Become Small And Vertical Data In The End?

Several years ago, I got to participate in one of the first neural net conferences. At the time, I thought it was amazing just to be there. There were chip and software vendors galore. Many even claimed to be the next Intel or the next Microsoft. Years later I joined a complex event processing vendor. Again, I felt the same sense of excitement. In both cases, the market participants moved from large horizontal market plays to smaller and more vertical solutions.

deja vuA sense of deja vu

Now to be clear, it is not my goal today to pop anyone’s big data balloon. But as I have gotten more excited about big data, I have gotten more and more an eerie sense of deja vu. The fact is the more that I dig into big data and hear customer’s stories about what they are trying to do with big data; the more I have concern about the similarities between big data and neural nets and complex event processing.

big dataBig Data offers new features

Clearly, big data does offer some interesting new features. And big data does take advantage of other market trends including virtualization and cloud. By doing so, big data achieves new orders of scalability than traditional business intelligence processing and storage. At the same time, big data offers the potential for lowering cost but I should take a moment to stress the word potential. The reason I do this is that while a myriad of processing approaches have been developed, no standard has yet emerged. And early adopters complain about having a difficulty in hiring big data map reduce programmers. And just like neural nets, the programing that needs to be done is turning out to be application specific.

With this said, it should be clear that big data does offer the potential to test datasets and to discover new and sometimes unexpected data relationship. This is a real positive thing. However, like its predecessors, this work is application specific and the data that is being related is truly of differing quality and detail. This means that the best that big data can do as a technology movement is discover potential data relationship. Once this is done, meaning can only be created by establishing detailed data relationships and dealing with the varying quality of data sets within the big data cluster.

Big Data will become small for management analysis

This means that big data must become small in order to really solve customer problems. Judith Hurwitz puts it this way, “big data analysis is really about small data. Small data, therefore, is the product of big data analysis. Big data will become small so that it is easier to comprehend”. What is “more necessary than ever is the capability to analyze the right data in a timely enough fashion to make decisions and take actions”. Judith says that in the end what is needed is quality data that is consistent, accurate, reliable, complete, timely, reasonable, and valid. The critical point is whether you use map reduce processing or traditional BI means, you shouldn’t throw out your data integration and quality tools. As big data becomes smaller, these will in reality become increasingly important.

So how does Judith see big data evolving? Judith sees big data propelling a lot of new small data. Judith believes that, “getting the right perspective on data quality can be very challenging in the world of big data. With a majority of big data sources, you need to assume that you are working with data that is not clean”. Judith says that we need to accept the fact that a lot of noise will exist in data. It is by searching and pattern matching that you will be able to find some sparks of truth in the midst of some very dirty data”. Judith suggests, therefore, a two phase approach—1) look for patterns in big data without concern for data quality; and 2) after you locate your patterns, applying the same data quality standards that have been applied to traditional data sources.

history repeatsHistory will repeat itself

For this reason, I believe that history will to a degree repeat itself. Clearly, the big data emperor does have his clothes on, but big data will become smaller and more vertical. Big data will become about relationship discovery and small data will become about quality analysis of data sources. In sum, this means that small data analysis is focused and provides the data for business decision making and big data analysis is broad and is about discovering what data potentially relates to what data.  I know this is a bit of different from the hype but it is realistic and makes sense. Remember, in the end, you will still need what business intelligence has refined.

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Big Data Why?

Business leaders share with Fortune Magazine their view of Big Data

FortuneFortune Magazine recently asked a number of business leaders about what Big Data means to them. These leaders provide three great stories for the meaning of Big Data. Phil McAveety at Starwood Hotels talked about their oldest hotel having a tunnel between the general manager’s office and the front desk. This way the general manager could see and hear new arrivals and greet each like an old friend. Phil sees Big Data as a 21st century version of this tunnel. It enables us to know our guests and send them offers that matter to them. Jamie Miller at GE says Big Data is being about transforming how they service their customers while simplifying the way they run their company. Finally, Ellen Richey at VISA says that big data holds the promise of making new connections between disperse bits of information creating value.

Everyone is doing it but nobody really knows why?

gravityI find all of these definitions interesting, but they are all very different and application specific. This isn’t encouraging. The message from Gartner is even less so. They find that “everyone is doing it but nobody really knows why”. According to Matt Asay, “the gravitational pull of Big Data is now so strong that even people who haven’t a clue as to what it’s all about report that they are running Big Data projects”. Gartner found in their research that 64% of enterprises surveyed say they’re deploying or planning to deploy Big Data projects. The problem is that 56% of those surveyed are struggling trying to determine how to get value out of big data, and 23% of those surveyed are struggling at how to define Big Data. Hopefully, none of the latter are being counted in the 64%. . Regardless, Gartner believes that the number of companies with Big Data projects is only going to increase. The question is how many of projects are just a recast of an existing BI project in order to secure funding or approval. No one will ever know.

Managing the hype phase of Big Data

hypeOne CIO that we talked to worries about this hype phase of Big Data. He says the opportunity is to inform analytics and guiding and finding business value. However, worries whether past IT mistakes will repeat themselves. This CIO believes that IT has gone through three waves. IT has grown from homegrown systems to ERP to Business Intelligence/Big Data. ERP was supposed to solve all the problems of the homegrown solutions but it did not provide anything more than information on transactions. You could not understand what is going on out there with ERP. BI and Big Data is trying to  go after this. However, this CIO worries that CEOs/CFOs will soon start complaining that the information garnered does not make the business more money. He worries that CEOs and CFOs will start effectively singing the Who song, “We won’t get fooled again.”

This CIO believes that to make more money, Big Data needs to connect the dots between transactional systems, BI, and planning systems. It needs to convert data into business value. This means Big Data is not just another silo of data, but needs to be connected and correlated to the rest of your data landscape to make it actionable. To do this, he says it needs to be proactive and cut the time to execution. It needs to enable the enterprise to generate value different than competitors. This, he believes mean that it needs to orchestrate activities so they maximize profit or increase customer satisfaction. You need to get to the point where it is sense and response. Transactional systems, BI, and planning systems need to provide intelligence to allow managers to optimize business processes execution. According to Judith Hurwitz, optimization is about establishing the correlation between streams of information and matching the resulting pattern with defined behaviors such as mitigating a threat or seizing an opportunity.”

Don’t leave your CEO and CFO with a sense of deja vu

dejavuIn sum, Big Data needs to go further in generating enough value to not leave your CEO and CFO with a sense of deja vu. The question is do you agree? Do you personally have a good handle on what Big Data is? And lastly, do you fear a day when the value generated needs to be attested to?

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How CFOs can change the conversation with their CIO?

Recently, I had the opportunity to interview half dozen CIOs and half dozen CFOs. Kind of like a marriage therapist, I got to see each party’s story about the relationship. CFOs, in particular, felt that the quality of the relationship could impact their businesses’ success. Armed with this knowledge, I wanted to see if I could help each leader build a better working relationship. Previously, I let CIO’s know about the emergence and significance of the strategic CFO.  In today’s post, l will start by sharing the CIOs perspective on the CFO relationship and then I will discuss how CFOs can build better CIO relationships.

CIOs feel under the gun these days!

Under the gunIf you don’t know, CIOs feel under the gun these days. CIOs see their enterprises demanding ubiquitous computing. Users want to use their apps and expect corporate apps to look like their personal apps such as Facebook. They want to bring their own preferred devices. Most of all, , they want all their data on any device when they need it. This means CIOs are trying to manage a changing technical landscape of mobile, cloud, social, and big data. These are all vying for both dollars and attention. As a result, CIOs see their role in a sea change. Today, they need to focus less on building things and more on managing vendors. CIOs say that they need to 1) better connect what IT is doing to support the business strategy;  2) improve technical orchestration; and 3) improve process excellence. This is a big and growing charter.

CIOs see the CFO conversation being just about the numbers

Only about the numbersCIOs worry that you don’t understand how many things are now being run by IT and that historical percentages of revenue may no longer appropriate. Think about healthcare, which used to be a complete laggard in technology but today it is having everything digitalized. Even a digital thermometer plugs into an iPad so it directly communicates with a patient record. The world has clearly changed. And CIOs worry that you view IT as merely a cost center and that you do not see the value generated through IT investment or the asset that information provides to business decision makers. However, the good news is that I believe that a different type of discussion is possible. And that CFOs have the opportunity to play an important role in helping to shape the value that CIOs deliver to the business.

CFOs should share their experience and business knowledge

Business ExperienceCFOs that I talked to said that they believe the CFO/CIO relationship needs to be complimentary and that the roles have the most concentric rings. These CFOs believe that the stronger the relationship the better it is for their business. One area that you can help the CIO is in sharing your knowledge of the business and business needs. CIOs are trying to get closer to the business and you can help build this linkage and to support requests that come out of this process. Clearly, an aligned CFO can be “one of the biggest advocates of the CIO”. Given this, make sure that you are on your CIOs Investment Committee.

 Tell your CIO about your data pains

Manual data movementCFOs need to be good customers too. CFOs that I talked to told me that they know their business has “a data issue”. They worry about the integrity of data from the source. CFOs see their role as relying increasingly on timely, accurate data. They, also, know they have disparate systems and too much manual stuff going on in the back office. For them, integration needs to exist from the frontend to the backend. Their teams personally feel the large number of manual steps.

For this reasons, CFOs, we talked to, believe that the integration of data is a big issue whether they are in a small or large business. Have you talked to your CIO about data integration or quality projects to change the ugliness that you have to live with day in day out? It will make you and the business more efficient. One CFO was blunt here saying “making life easier is all about the systems. If the systems suck then you cannot trust the numbers when you get them. You want to access the numbers easily, timely, and accurately. You want to make easier to forecast so you can set expectations with the business and externally”.

At the same time, CFOs that I talked to worried about the quality of financial and business data analysis. Once he had data, he worried about being able to analyze information effectively. Increasingly, CFOs say that they need to help drive synergies across their businesses. At the same time, CFOs increasingly need to manage upward with information.  They want information for decision makers so they can make better decisions.

Changing the CIO Dialog

So it is clear that CFOs like you see data as a competitive advantage in particular financial data. The question is, as your unofficial therapist, why aren’t you having a discussion with your CIO not just about the numbers or financial justification for this or that system and instead, asking about the+ integration investment that can make your integration problems go away.

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New type of CFO represents a potent CIO ally

The strategic CFO is different than the “1975 Controller CFO”

CFOTraditionally, CIOs have tended to work with what one CIO called a “1975 Controller CFO”. For this reason, the relationship between CIOs and CFOs was expressed well in a single word “contentious”. But a new type of CFO is emerging that offers the potential of different type of relationship. These so called “strategic CFOs” can be an effective ally for CIOs. The question is which type of CFO do you have? In this post, I will provide you with a bit of a litmus test so you can determine what type of CFO you have but more importantly, I will share how you can take maximum advantage of having a strategic-oriented CFO relationship. But first let’s hear a bit more of the CIOs reactions to CFOs.

Views of CIOs according to CIO interviews

downloadClearly, “the relationship…with these CFOs is filled with friction”. Controller CFOs “do not get why so many things require IT these days. They think that things must be out of whack. One CIO said that they think technology should only cost 2-3% of revenue while it can easily reach 8-9% of revenue these days.” Another CIO complained by saying their discussion with a Controller CFOs is only about IT productivity and effectiveness. In their eyes, this has limited the topics of discussion to IT cost reduction, IT produced business savings, and the soundness of the current IT organization. Unfortunately, this CIO believe that Controller CFOs are not concerned with creating business value or sees information as an asset. Instead, they view IT as a cost center. Another CIO says Controller CFOs are just about the numbers and see the CIO role as being about signing checks. It is a classic “demand versus supply” issue. At the same times, CIOs say that they see reporting to Controller CFO as a narrowing function. As well, they believe it signals to the rest of the organization “that IT is not strategic and less important than other business functions”.

What then is this strategic CFO?

bean counterIn contrast to their controller peers, strategic CFOs often have a broader business background than their accounting and a CPA peers. Many have, also, pursued an MBA. Some have public accounting experience. Others yet come from professions like legal, business development, or investment banking.

More important than where they came from, strategic CFOs see a world that is about more than just numbers. They want to be more externally facing and to understand their company’s businesses. They tend to focus as much on what is going to happen as they do on what has happened. Remember, financial accounting is backward facing. Given this, strategic CFOs spend a lot of time trying to understand what is going on in their firm’s businesses. One strategic CFO said that they do this so they can contribute and add value—I want to be a true business leader. And taking this posture often puts them in the top three decision makers for their business. There may be lessons in this posture for technology focused CIOs.

Why is a strategic CFO such a game changer for CIO?

Business DecisionsOne CIO put it this way. “If you have a modern day CFO, then they are an enabler of IT”. Strategic CFO’s agree. Strategic CFOs themselves as having the “the most concentric circles with the CIO”. They believe that they need “CIOs more than ever to extract data to do their jobs better and to provide the management information business leadership needs to make better business decisions”. At the same time, the perspective of a strategic CFO can be valuable to the CIO because they have good working knowledge of what the business wants. They, also, tend to be close to the management information systems and computer systems. CFOs typically understand the needs of the business better than most staff functions. The CFOs, therefore, can be the biggest advocate of the CIO. This is why strategic CFOs should be on the CIOs Investment Committee. Finally, a strategic CFO can help a CIO ensure their technology selections meet affordability targets and are compliant with the corporate strategy.

Are the priorities of a strategic CFO different?

Strategic CFOs still care P&L, Expense Management, Budgetary Control, Compliance, and Risk Management. But they are also concerned about performance management for the enterprise as whole and senior management reporting. As well they, they want to do the above tasks faster so finance and other functions can do in period management by exception. For this reason they see data and data analysis as a big issue.

Strategic CFOs care about data integration

In interviews of strategic CFOs, I saw a group of people that truly understand the data holes in the current IT system. And they intuit firsthand the value proposition of investing to fix things here. These CFOs say that they worry “about the integrity of data from the source and about being able to analyze information”. They say that they want the integration to be good enough that at the push of button they can get an accurate report. Otherwise, they have to “massage the data and then send it through another system to get what you need”.

These CFOs say that they really feel the pain of systems not talking to each other. They understand this means making disparate systems from the frontend to the backend talk to one another. But they, also, believe that making things less manual will drive important consequences including their own ability to inspect books more frequently. Given this, they see data as a competitive advantage. One CFO even said that they thought data is the last competitive advantage.

Strategic CFOs are also worried about data security. They believe their auditors are going after this with a vengeance. They are really worried about getting hacked. One said, “Target scared a lot of folks and was to many respects a watershed event”. At the same time, Strategic CFOs want to be able to drive synergies across the business. One CFO even extolled the value of a holistic view of customer. When I asked why this was a finance objective versus a marketing objective, they said finance is responsible for business metrics and we have gaps in our business metrics around customer including the percentage of cross sell is taking place between our business units. Another CFO amplified on this theme by saying that “increasingly we need to manage upward with information. For this reason, we need information for decision makers so they can make better decisions”. Another strategic CFO summed this up by saying “the integration of the right systems to provide the right information needs to be done so we and the business have the right information to manage and make decisions at the right time”.

So what are you waiting for?

If you are lucky enough to have a Strategic CFO, start building your relationship. And you can start by discussing their data integration and data quality problems. So I have a question for you. How many of you think you have a Controller CFO versus a Strategic CFO? Please share here.

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The Business Case for Better Data Connectivity

andyAfter I graduated from business school, I started reading Fortune Magazine. I guess that I became a regular reader because each issue largely consists of a set of mini-business cases. And over the years, I have even started to read the witty remarks from the managing editor, Andy Serwer. However, this issue’s comments were even more evocative than usual.

Connectivity is perhaps the biggest opportunity of our time

Andy wrote, “Connectivity is perhaps the biggest opportunity of our time. As technology makes the world smaller, it is clear that the countries and companies that connect the best—either in terms of, say traditional infrastructure or through digital networks are in the drivers’ seat”. Andy sees differentiated connectivity as involving two elements–access and content. This is important to note because Andy believes the biggest winners going forward are going to be the best connectors to each.

Enterprises need to evaluate how the collect, refine, and make useful data

But how do enterprises establish world class connectivity to content? I would argue–whether you are talking about large or small data—it comes from improving an data connectivityenterprise’s abiity collect, refine, and create useful data. In recent CFO research, the importance of enterprise data gathering capabilities was stressed. CFOs said that their enterprises need to “get data right” at the same time as they confirmed that their enterprises in fact have a data issue. The CFOs said that they are worried about the integrity of data from the source forward. And once they manually create clean data, they worry about making this data useful to their enterprises. Why does this data matter so much to the CFO? Because as CFOs get more strategic, they are trying to make sure their firms drive synergies across their businesses.

Business need to make sense of data and get it to business users faster

One CFO said it this way, “data is potentially the only competitive advantage left”. Yet another said, “our businesses needs to make better decisions from data. We need to make sense of data faster.” At the same time leading edge thinkers like Geoffrey Moore has been mooresuggesting that businesses need to move from “systems of record” applications to “system of engagement” applications. This notion suggests the importance of providing more digestible apps, but also the importance of recognizing that the most important apps for business users will provide relevant information for decision making. Put another way, data is clearly becoming fuel to the enterprise decision making.

“Data Fueled Apps” will provide a connectivity advantage

For this reason, “data fueled” apps will be increasingly important to the business. Decision makers these days want to practice “management by walking around” to quote Tom Walking aroundPeter’s Book, “In Search of Excellence”. And this means having critical, fresh data at their fingertips for each and every meeting. And clearly, organizations that provide this type of data connectivity will establish the connectivity advantage that Serwer suggested in his editor comments. This of course applies to consumer facing apps as well. Server, also, comments on the impacts of Apple and Facebook. Most consumers today are far better informed before they make a purchase.  The customer facing apps, for example Amazon, that have led the way have provided the relevant information for the consumer to inform them on their purchase journey.

Delivering “Data Fueled Apps” to the Enterprise

But how do you create the enterprise wide connectivity to power the “Data Fueled Apps?”  It is clear from the CFOs comments work is needed here. That work involves creating data which is systematically clean, safe, and connected. Why does this data need to be clean? The CFOs we talked to said that when the data is not clean then they have to manually massage the data and then move from system to system. This is not providing the kind of system of engagement envisioned by Geoffrey Moore. What this CFO wants to move to a world where he can access the numbers easily, timely, and accurately”.

Data, also, needs to be safe. This means that only people with access should be able to see data whether we are talking about transactional or analytical data. This may sound obvious, but very few isolate and secure data as it moves from system to system. And lastly, data needs to be connected. Yet another CFO said, “the integration of the right systems to provide the right information needs to be done so we have the right information to manage and make decisions at the right time”. He continued by saying “we really care about technology integration and getting it less manual. It means that we can inspect the books half way through the cycle. And getting less manual means we can close the books even faster. However, if systems don’t talk (connect) to one another, it is a big issue”.

Finally, whether we are discussing big data or small data, we need to make sure the data collected is more relevant and easier to consume.  What is needed here is a data intelligence layer provides easy ways to locate useful data and recommend or guide ways to improve the data. This way analysts and leaders can spend less time on searching or preparing data and more time on analyzing the data to connect the business dots. This can involve mapping data relationship across all applications and being able to draw inferences from data to drive real time responses.

So in this new connected world, we need to first set up a data infrastructure to continuously make data clean, safe, and connected regardless of use case. It might not be needed to collect data, but the data infrastructure may be needed to define the connectivity (in the shape of access and content). We also need to make sure that the infrastructure for doing this is reusable so that the time from concept to new data fueled app is minimized. And then to drive informational meaning, we need to layer on top the intelligence. With this, we can deliver “data fueled apps” that enable business users the access and content to drive better business differentiation and decisioning!

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Creating a Differentiated Retail Customer Experience

Michael Porter

Michael Porter

In my marketing classes, I like to share on the works of Michael Porter’s Competitive Strategy. This includes discussing his three generic business strategies. We discuss, for example, the difference between an “efficiency strategy” (aka Walmart) and an “effectiveness strategy” (aka Target or even better, a high end service oriented retailer). I always make sure that students include in their thinking on differentiation the impact of customer service.

customer service One of these high end service oriented retailers is using technology to increase its customer intimacy as well as holistic customer knowledge. Driving this for them involves understanding when customers use their full price and off price customer purchase channels. I was so fascinated about their question that I decided to ask the font of all wisdom, my wife. She said that her choice of channel is based on my current salary or her projected length of use of an item. So if she is buying a jacket that she wants to use for years, she will go to the full price channel but for a dress or pair of shoes for one time use like a Wedding, she will go to the lower priced channel. Clearly, there is more than one answer to these questions. This retailer wants to understand the answers by customer segments.

singleviewTo create an understanding of each customer segment, this retailer wants to create a “high fidelity” view of data coming from customers, markets, and transactional interactions. This means that that they need two new business capabilities. First is a single integrated view of their customers across channels and the ability to see the cause and effect of customer channel selection decisions. Do customers spend more time at the full price channel option when, for example, sale offerings are going on?

To solve these problems, the retailer has implemented two technology approaches, master data management to bring together its disparate views of customer and big data for quick hypothesis testing of customer data from structured and unstructured sources. With Master Data, they get a single view of customer across differing IT systems. For separate customer specific analysis they have created operational and analytic views on top of the MDM system. And while they have an enterprise data warehouse and multiple analytical data marts, they have also created a HADOOP cluster to test hypothesis about the cross channel customer segments. They are using the single view of customer regardless of channels and transaction history to understand when customers use which channel and as well what marketing or other campaigns pulled the customer in. With this, they are creating inferred attributes for customer market segments.

Clearly, the smarter the retailer gets, the greater the differentiation the retailer services can be to customers. At the same time, the data let’s the retailer optimize marketing between channels. This is using data to create service differentiation.

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Major Financial Services Institution uses technology to improve your teller experience

Financial Services

Major Financial Services Institution uses technology to improve your teller experience

Like many American men, I judge my banking experience by the efficiency of my transaction time. However, my wife often still likes to go into the bank and see her favorite teller.

For her, banking is a bit more of a social experience. And every once in a while, my wife even drags into her bank as well.  But like many of my male counterparts, I still judge the quality of the experience by the operational efficiency of her teller. And the thing that I hate the most is when our experience at the bank is lengthened when the teller can’t do something and has to get the bank manager’s approval.

Now, a major financial institution has decided to make my life and even my wife’s life better. Using Informatica Rulepoint, they have come up with a way to improve teller operational efficiency and customer experience while actually decreasing operational business risks. Amazing!

How has this bank done this magic? They make use of the data that they have to create a better banking experience. They already capture historical transactions data and team member performance against each transaction in multiple databases. What they are doing now is using this information to make better decisions. With this information, this bank is able to create and update a risk assessment score for each team member at a branch location. And then by using Informatica Rulepoint, they have created approximately 100 rules that are able change teller’s authority based upon the new transaction, the teller’s transaction history, and the teller’s risk assessment score. This means that if my wife carefully picks the right teller, she is speed through the line without waiting for management approval.

So the message at this bank is the fastest teller is the best teller. To me this is really using data to improve  customer experience and allow for less time in a line. Maybe I should get this bank to talk next to my auto mechanic!

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What is big data and why should your business care?

Big data is different than small data

The definitions of big data are diverse. Many authors define big data by its characteristics–volume, velocity, and variety of data. VC Choudary, Associate Professor of Information Systems at UCI, for example, says “what differentiates Big Data from traditional data is the sheer volume of information, velocity at which it is created, and the variety of sources from which it is drawn?” Hurwitz and Associates—a BI consultancy—defines Big Data similarly as the capability to manage a huge volume of disparate data, at the right speed, and within the right time frame to allow real time analysis and reaction.

But how about the business practitioner’s point of view? Recently, I heard a significant Healthcare CIO talk about Big Data. This CIO defined Big Data by defining what is “small data” first. He said small data is “single-source, often batch-processed, and locally managed”. So what then is Big Data? “It is multi-source, requires connecting between data sources, multi-structured (structured and unstructured), real time, and uses information in aggregate”. This healthcare CIO went onto say that he sees “Big Data aiming to establish a model from the data. Big Data is about finding data relationships in the data rather than creating the data relationships in a data model”. This is a huge difference from traditional business intelligence (BI), which is best implemented when there is a level of determinism for the data in the data model.

Parallel architectures enable Big Data

Truly parallel architectures are an enabler of Big Data. To be fair, parallel architectures are not truly new—parallel architectures have existing for some time. I remember seeing my first server based parallel architecture in the work that Intel and other chipset makers were doing back in the mid 90s. And to be really fair Von Neumann defined parallel processing and serial processing architectures at the same time. What is new is that over the last few years is that we have lost a degree of parallelism as we have sought to centralize and protect data. What Hadoop does is to gang bang together many cheap machines at the same time as it spreads the data and spreads the processing. Redundancy is achieved by sharing each processing load with more than one machine.

Big Data moves from descriptive statistics to predictive analytics

According to Choudary, Big Data is not just about the amount of data that can be processed. It also about what you can do with data. He claims that “Big Data is about changing the game of business from one of simple descriptive statistics into one where all of the available data is collected and mined together. The Big Data era is about predicting outcomes based on disparate pieces of information and therefore, it is about prescribing opportunities.”

Real Life Big Data Case Studies

So what is big data good for?

Let’s start with what has already been learned in healthcare big data analysis. In healthcare, they have found that people with higher pain scores crash more often in the ICU. Scary to me that they are just learning this! Another big issue in healthcare is re-admits. And Healthcare reform creates big penalties for them. To help limit them, it is really important that know that patients manage their illness after they leave the hospitals. What they have learned from studying patient credit scores, is that they are a good predictor of whether patients will take their medicines and therefore, have a tendency to be readmitted to the hospital. The higher the credit score, the higher the probability is that people will take their medicine after leaving the hospital. I found this particularly interesting, because several years ago, I got to work with Intuit. They had identified a persona for those that were meticulous with their finances. They called them anal-retentives. Big Data has determined that anal-retentives take their medicines more often. So hospitals should check-in more regularly on those with poor credit scores to make sure that they are taking their medicines and thus, limit their re-admits.

The Healthcare CIO that we mentioned earlier claims that Big Data will over time move from “differentiating healthcare organizations to table stakes.” When I asked him why, he said the reason is simple: “We are in the business of creating the highest value care. And big data is fundamentally about serving our patients better than we do today. And everyone in healthcare will have to do it.” Another Healthcare CIO says that he is looking to Big Data to help him create a greater understanding of the relationship of inputs to outputs concerning patients. We need to have a better understanding of the health status and needs of a specific patient over time. This means assembling data from multiple patient encounters and multiple sources. He goes on to say that “those organizations with strong partnerships up and down the value chain or for that matter, even among competitors, are better positioned to take insights, process improvements, and other advantages to the market. Use and management of data and will increasingly become an element of competitive advantage”.

Big Data helps with Credit Risk

It is not just healthcare that sees big changes being enabled by Big Data, the president of a major credit reporting agency sees Big Data as enabler of risk reduction for his firms. He asserts as well that on average firms use less than 5% of the data available to them—this is important in financial markets where the quality of risk management can to determine the earnings returned to shareholders. He says, however, he sees a challenge in big data is hiring the talented people who can ask the right questions of data. As in many growth industries, hiring talented practitioners and data scientist is a difficult thing to do.

Big Data makes Fast Food Better

Meanwhile, a major fast food vendor says that big data has enabled them to better understand their market from the outside in and across many disciplines including public relations, customer service, marketing, advertising, research, product innovation, and sales. Clearly, creating a view across all these touch points can lead to better decision making.

What does it mean?

So there you have it. Big Data is big in terms of what it involves and what it is trying to accomplish. It has already had derived interesting outcomes for healthcare, credit reporting, and even fast food. The question is what is doing or can do for your business. Please feel share to your results here.

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