Why now? Because companies need help making sense of the data deluge, Salesforce’s CEO Marc Benioff said at Dreamforce: “Did you know 90% of the world’s data was created in the last two years? There’s going to be 10 times more mobile data by 2020, 19 times more unstructured data, and 50 times more product data by 2020.” Average business users want to understand what that data is telling them, he said. Given Salesforce’s marketing expertise, this could be the spark that gets mainstream businesses to adopt the Data-First perspective I’ve been talking about.
As I’ve said before, a Data First POV shines a light on important interactions so that everyone inside a company can see and understand what matters. As a trained process engineer, I can tell you, though, that good decisions depend on great data — and great data doesn’t just happen: At the most basic level, you have to clean it, relate it, connect and secure it — so that information from, say, SAP, can be viewed in the same context as data from Salesforce. Informatica obviously plays a role in this. If you want to find out more, click on this link to download our Salesforce Integration for Dummies brochure.
But that’s the basics for getting started. The bigger issue — and the one so many people seem to have trouble with — is deciding which metrics to explore. Say, for example, that the sales team keeps complaining about your marketing leads. Chances are, it’s a familiar complaint. How do you discover what’s really the problem?
One obvious place to start to first look at the conversation rates for every sales rep and group. Next explore the marketing leads they do accept such as deal size, product type or customer category. Now take it deeper. Examine which sales reps like to hunt for new customers and which prefer to mine their current base. That will tell you if you’re sending opportunities to the right profiles.
The key is never looking at the sales organization as a whole. If it’s EMEA, for instance, have a look to see how France is doing selling to emerging markets vs. the team in Germany. These metrics are digital trails of human behavior. Data First allows you to explore that behavior and either optimize it or change it.
But for this exploration to pay off, you actually have to do some of the work. You can’t just job it out to an analyst. This exercise doesn’t become meaningful until you are mentally engaged in the process. And that’s how it should be: If you are a Data First company, you have to be a Data First leader.
The way I see it, the biggest impact of the Apple Watch will come from how it will finally make data fashionable. For starters, the three Apple Watch models and interchangeable bands will actually make it hip to wear a watch again. But I think the ramifications of this genuinely good-looking watch go well beyond the skin deep. The Cupertino company has engineered its watch and its mobile software to recognize related data and seamlessly share it across relevant apps. And those capabilities allow it to, for instance, monitor our fitness and health, show us where we parked the car, open the door to our hotel room and control our entertainment centers.
Think what this could mean for any company with a Data-First point of view. I like to say that a data-first POV changes everything. With it, companies can unleash the killer app, killer marketing campaign and killer sales organization.The Apple Watch finally gives people a reason to have that killer app with them at all times, wherever they are and whatever they’re doing. Looked at a different way, it could unleash a new culture of Data-Only consumers: People who rely on being told what they need to know, in the right context.
But while Apple may the first to push this Data-First POV in unexpected ways, history has shown they won’t be the last. It’s time for every company to tap into the newest fashion accessory, and make data their first priority.
You probably know this already, but I’m going to say it anyway: It’s time you changed your infrastructure. I say this because most companies are still running infrastructure optimized for ERP, CRM and other transactional systems. That’s all well and good for running IT-intensive, back-office tasks. Unfortunately, this sort of infrastructure isn’t great for today’s business imperatives of mobility, cloud computing and Big Data analytics.
Virtually all of these imperatives are fueled by information gleaned from potentially dozens of sources to reveal our users’ and customers’ activities, relationships and likes. Forward-thinking companies are using such data to find new customers, retain existing ones and increase their market share. The trick lies in translating all this disparate data into useful meaning. And to do that, IT needs to move beyond focusing solely on transactions, and instead shine a light on the interactions that matter to their customers, their products and their business processes.
They need what we at Informatica call a “Data First” perspective. You can check out my first blog first about being Data First here.
A Data First POV changes everything from product development, to business processes, to how IT organizes itself and —most especially — the impact IT has on your company’s business. That’s because cloud computing, Big Data and mobile app development shift IT’s responsibilities away from running and administering equipment, onto aggregating, organizing and improving myriad data types pulled in from internal and external databases, online posts and public sources. And that shift makes IT a more-empowering force for business change. Think about it: The ability to connect and relate the dots across data from multiple sources finally gives you real power to improve entire business processes, departments and organizations.
I like to say that the role of IT is now “big I, little t,” with that lowercase “t” representing both technology and transactions. But that role requires a new set of priorities. They are:
- Think about information infrastructure first and application infrastructure second.
- Create great data by design. Architect for connectivity, cleanliness and security. Check out the eBook Data Integration for Dummies.
- Optimize for speed and ease of use – SaaS and mobile applications change often. Click here to try Informatica Cloud for free for 30 days.
- Make data a team sport. Get tools into your users’ hands so they can prepare and interact with it.
I never said this would be easy, and there’s no blueprint for how to go about doing it. Still, I recognize that a little guidance will be helpful. In a few weeks, Informatica’s CIO Eric Johnson and I will talk about how we at Informatica practice what we preach.
That second question is a killer because most people — no matter if they’re in marketing, sales or manufacturing — rely on incomplete, inaccurate or just plain wrong information. Regardless of industry, we’ve been fixated on historic transactions because that’s what our systems are designed to provide us.
“Moneyball: The Art of Winning an Unfair Game” gives a great example of what I mean. The book (not the movie) describes Billy Beane hiring MBAs to map out the factors that would win a baseball game. They discovered something completely unexpected: That getting more batters on base would tire out pitchers. It didn’t matter if batters had multi-base hits, and it didn’t even matter if they walked. What mattered was forcing pitchers to throw ball after ball as they faced an unrelenting string of batters. Beane stopped looking at RBIs, ERAs and even home runs, and started hiring batters who consistently reached first base. To me, the book illustrates that the most useful knowledge isn’t always what we’ve been programmed to depend on or what is delivered to us via one app or another.
For years, people across industries have turned to ERP, CRM and web analytics systems to forecast sales and acquire new customers. By their nature, such systems are transactional, forcing us to rely on history as the best predictor of the future. Sure it might be helpful for retailers to identify last year’s biggest customers, but that doesn’t tell them whose blogs, posts or Tweets influenced additional sales. Isn’t it time for all businesses, regardless of industry, to adopt a different point of view — one that we at Informatica call “Data-First”? Instead of relying solely on transactions, a data-first POV shines a light on interactions. It’s like having a high knowledge IQ about relationships and connections that matter.
A data-first POV changes everything. With it, companies can unleash the killer app, the killer sales organization and the killer marketing campaign. Imagine, for example, if a sales person meeting a new customer knew that person’s concerns, interests and business connections ahead of time? Couldn’t that knowledge — gleaned from Tweets, blogs, LinkedIn connections, online posts and transactional data — provide a window into the problems the prospect wants to solve?
That’s the premise of two startups I know about, and it illustrates how a data-first POV can fuel innovation for developers and their customers. Today, we’re awash in data-fueled things that are somehow attached to the Internet. Our cars, phones, thermostats and even our wristbands are generating and gleaning data in new and exciting ways. That’s knowledge begging to be put to good use. The winners will be the ones who figure out that knowledge truly is power, and wield that power to their advantage.
We can all imagine self-driving cars that distinguish between a life-threatening situation (like a swerving car ahead) or a thing-threatening occurrence (like a scurrying raccoon) and brake and steer accordingly. And we expect automated picking systems will soon know — by a SKU’s size, shape, weight and temperature — which assembly line or packing area gets which products. And it won’t be long before enterprise systems will see and plug security holes across hundreds of systems, no matter whether the data is hosted internally or held by partners and suppliers.
The underpinning for such smarts is data that’s clean, safe and connected — the hallmarks of everything we do and believe in at Informatica. But we also recognize that next-generation products need something more. They also need to know when and where data changes, along with how to get the right data to the right person, place or thing, in the right way. That’s why Informatica is unveiling our vision for an Intelligent Data Platform, fueled by new technology innovations in data intelligence.
Data intelligence is built on two new capabilities – live data map and inference engine. Live data map continuously updates all the metadata—structural, semantic, usage and otherwise— on all of the data flowing through an enterprise, while the inference engine can deduce user intentions, help humans search for what they need in their own natural language, and provide recommendations on the best way to consume data depending on the use case. The combination ensures that clean, safe and connected data gets to whomever or whatever needs it, as it’s needed—fast.
We at Informatica believe these capabilities are so incredibly vital for the enterprise that the Intelligent Data Platform now serves as the foundation of many of our future products — beginning with Project Springbok and Project Secure@Source™. These two new offerings simplify some of the toughest challenges facing people in the enterprise: letting business users find and use the data they need, and seeing where their most-sensitive data is hiding amidst all the nooks and crannies.
Project Springbok’s Excel-like interface lets everyday business folks and mere mortals find the data sets they’re interested in, fix formatting and quality issues, and do tasks that are a pain today to perform — such as combining data sets or publishing the results for colleagues to reuse and enhance. Project Springbok is also a guide, with its recommendations derived by the inference engine. It tells users the sources they could or should have access to, and then provisions only what they should have. It lets users see which data sets colleagues are most frequently accessing and finding the most valuable. It also alerts users to inconsistent or incomplete data, suggests ways to sort new combinations of data sets and recommends the best data for the task.
While we designed Project Springbok for the average business user, Project Secure@Source is intended for people responsible for protecting the enterprise, including chief risk officers, chief information security officers (CISOs) and even board members of public companies. That’s because Project Secure@Source’s graphical interface displays all the systems holding sensitive data, such as social security numbers, medical records or payment card information.
But it’s not enough just to know where that data is. To safeguard all the sensitive information about their products, their customers, and their employees, users also need to understand how that data got into these systems, how it moves around, and who is using it. Project Secure@Source does that, too — showing, for example, that an engineer used payment card data to test a Hadoop cluster, and left it there. With Project Secure@Source, users can selectively remove or mask that data from any system in the enterprise.
You’ll hear us talk about and showcase the Intelligent Data Platform, Project Springbok and Project Secure@Source at Informatica World on May 13 and 14. I hope you’ll join us to learn how our vision and our product roadmap will enable a smarter world for all of us, today.
Sure, from May 12 – 14, you’ll be immersed in Information Architectures, Cloud Strategies, and Big Data at more than 100 in-depth sessions. You’ll network with data’s best and brightest, including Informatica visionaries and technical staff. And you’ll enjoy one-on-one time with us at the Hands-On Labs.
But on Thursday, it will be time to switch gears, think about data in entirely different ways, and have some fun, first with amazing keynotes:
- The Human Side of Data: Jer Thorp will show how cutting edge visualization techniques can be used to tell stories and make data more human.
- Data for Good: Drew Conway will push us to use and analyze data not just to increase efficiency and profits, but also to serve society and “do good.”
Then, enjoy a special performance from an indie rock sensation with an infectious and inventive style and sound.
It all happens at the Cosmopolitan Hotel, which Frommer’s Travel Guide calls “…audacious, bold, stunningly visual, and one of the most interesting hotels in Vegas or anywhere else for that matter.”
Book your room now when you register, so you won’t be hiking in from somewhere else. The cutoff date is April 23! Use the Scheduler to select your sessions, book Hands-On Lab time and build your calendar. Early registrants get the jump on the best schedule.
Register now and you can still choose a FREE Pre-Conference Day session on MDM, ILM, Cloud, or Informatica University.
People are obsessed with data. Data captured from our smartphones. Internet data showing how we shop and search — and what marketers do with that data. Big Data, which I loosely define as people throwing every conceivable data point into a giant Hadoop cluster with the hope of figuring out what it all means.
Too bad all that attention stems from fear, uncertainty and doubt about the data that defines us. I blame the technology industry, which — in the immortal words of Cool Hand Luke has had a “failure to communicate.” For decades we’ve talked the language of IT and left it up to our direct customers to explain the proper care-and-feeding of data to their business users. Small wonder it’s way too hard for regular people to understand what we, as an industry, are doing. After all, how we can expect others to explain the do’s and don’ts of data management when we haven’t clearly explained it ourselves?
I say we need to start talking about the ABC’s of handling data in a way that’s easy for anyone to understand. I’m convinced we can because — if you think about it — everything you learned about data you learned in kindergarten: It has to be clean, safe and connected. Here’s what I mean:
Data cleanliness has always been important, but assumes real urgency with the move toward Big Data. I blame Hadoop, the underlying technology that makes Big Data possible. On the plus side, Hadoop gives companies a cost-effective way to store, process and analyze petabytes of nearly every imaginable data type. And that’s the problem as companies go through the enormous time suck of cataloging and organizing vast stores of data. Put bluntly, big data can be a swamp.
The question is, how to make it potable. This isn’t always easy, but it’s always, always necessary. It begins, naturally, by ensuring the data is accurate, de-deduped and complete.
Now comes the truly difficult part: Knowing where that data originated, where it’s been, how it’s related to other data and its lineage. That data provenance is absolutely vital in our hyper-connected world where one company’s data interacts with data from suppliers, partners, and customers. Someone else’s dirty data, regardless of origin, can ruin reputations and drive down sales faster than you can say “Target breach.” In fact, we now know that hackers entered Target’s point-of-sales terminals through a supplier’s project management and electronic billing system. We won’t know for a while the full extent of the damage. We do know the hack affected one-third of the entire U.S. population. Which brings us to:
Obviously, being safe means keeping data out of the hands of criminals. But it doesn’t stop there. That’s because today’s technologies make it oh so easy to misuse the data we have at our disposal. If we’re really determined to keep data safe, we have to think long and hard about responsibility and governance. We have to constantly question the data we use, and how we use it. Questions like:
- How much of our data should be accessible, and by whom?
- Do we really need to include personal information, like social security numbers or medical data, in our Hadoop clusters?
- When do we go the extra step of making that data anonymous?
And as I think about it, I realize that everything we learned in kindergarten boils down to down to the ethics of data: How, for example, do we know if we’re using data for good or for evil?
That question is especially relevant for marketers, who have a tendency to use data to scare people, for crass commercialism, or to violate our privacy just because technology makes it possible. Use data ethically, and we can help change the use.
In fact, I believe that the ethics of data is such an important topic that I’ve decided to make it the title of my new blog.
Stay tuned for more musings on The Ethics of Data.
As 2014 is already upon us, here are Marge’s 2014 predictions:
- CMOs will actually be more data-driven than the CIOs: In 2014, CMOs will take over the lead from IT as the organization which most effectively collects, cleanses and leverages data about customers from a wide variety of sources from data bases, to CRM systems, to digital tools to gain a full picture of the customer base.
- Convergence of CIOs and CMOs: As marketers’ technology spend increases, CMOs are gaining more power in the digital space and consequently need to work with the CIO more and more. In 2014 we will see the emergence of a new hybrid role where the CIO and CMO role will merge—the chief digital officer.
- Social media’s equal share: As social media sites come of age, i.e. Twitter’s IPO, the CMOs budget in 2014 will be equally distributed between brand, lead generation and social media. Social media becomes equally important to lead generation and even drives more lead generation through the funnel than traditional marketing tactics.
- Marketing automation: more dollars will be spent for programs versus people as marketers drive to create more automated processes in the coming year. 75 percent of marketing will be automated, while 25 percent will be customer unique.
- Custom content: As more and more marketers are creating their own content to drive sales, the barriers between paid, earned and owned media will break down to one integrated content strategy. Currently, 43 percent have a documented strategy—next year more than 60 percent will.
- Redefining ROI: As new platforms for marketing content arise, the definition of ROI will shift to ROE—“Return on Engagement” with customers, turning content into leads and sales; metrics will shift from quantitative to qualitative. The CMO will deliver a social ROE report weekly to the CEO.
- Internet of Things: According to Forrester, 90 percent of consumers who have multiple connected devices switch between the devices to complete tasks—that’s a lot of machine data about consumers and their products. CMOs will need to spend one-third of their time analyzing data and using predictive analytics to make marketing decisions.
- The quantified self: In 2014, mobile will drive more than 50% of the traffic to organizations homepage. Companies will need to be mobile-first. With data being pulled from numerous devices and platforms, one winner will emerge in BI in marketing to help collate this information.
- Micro-content: Content will continue to get shorter—even after the boom of the six-second Vine video. Next year, try creating a brand message via a three-second video or a Snapchat photo that lasts on your device no longer than 24 hours.
- Collaboration continues to rule the world: next year the emergence of an entirely new set of collaboration tools will burst on the scene that can be leveraged across country and across time zones to make collaboration easier and seamless.
The Potential of Information to inform every one, everything, everywhere is upon us.
For nearly forty years, the term IT has been associated with professional advances in technology and applications. Transactional applications. Systems infrastructure. Network Infrastructure. Applications infrastructure. The irony lies in the fact that all of these technologies have aimed at centralization of information for business outcomes, yet they’ve addressed only 2 percent of the information challenge that employees face today. Most business processes and even the average employee spend only a few minutes of the day in a transactional application. The other 98% of the day is spent in interactions — meetings, analyzing data and collaborating with colleagues. And barely a fraction of the information potential that can be unleashed for people and connected devices has been realized. This year, nearly 4 billion people will be connected on the Internet. And by the year 2020, tens of billions of consumer and industrial devices or smart machines will be online. The potential of information to inform every one, everything, everywhere is upon us.
Information has always been the Killer App. The fourth wave is Information Discovery, Visibility, and Optimization..
The first wave of application development focused on management of business processes. Visibility of transactions. And the target audience was management. The second wave of applications became modernization of these apps for heightened user convenience on the Web or mobile devices—smaller, lighter-weight, intuitive applications. Software as a service (SaaS) was the third wave of applications. It became about user-centricity and near-zero footprint deployment. The fourth wave of applications is about the combination of business, consumer, and device information. These applications will discover the right information, deliver it at the right time to the right person, process, or device. With intuition, elegance, and ease. And improve it over and over again. These applications will be increasingly distributed and lightweight— much like the Internet. Like Java. Like Ethernet. A true information network with an infinitely scalable architecture.
The Information Network. It’s Really That Big. And Needs to Be Really That Small.
The fastest-growing asset class in enterprises, governments, and individuals is information. Digital media. Sensor data. Relationships. Doubling every year, it’s growing faster than Twitter. Faster than cell phones. Faster than the birth, retirement, or death rate.
And it’s increasingly fragmented. Mobile, social, SaaS, and global value chains have accelerated the fragmentation. And the holy grail of consumer, employee, and citizen behavior lives beyond the scope of any single big data cluster—no matter how big. It will be real-time. And batch. Structured and unstructured. For humans and machines. Information will live in a three-tier architecture. Housed in the data center. Aggregated in the field or at the large device. Collected at the point of data. In the device. On the factory floor. In the hospital room.
The Information Network. Architected by Design. Powered by Vibe.
In order to realize this vision, information needs infrastructure and this infrastructure must be built on architecture. Only architecture can handle the range in scale, the diversity, and the accessibility needed for a true information network.
We believe that the foundational element of the information network is Vibe. Vibe is the world’s first embeddable virtual data machine for accessing, aggregregating and managing data regardless of source or format. The scalable virtual data machine that today powers data centers, cloud connections, and analytics around the world. And soon, Vibe will power small businesses, departments, applications, and devices everywhere.
Our Mission. Our Vision. Our Purpose.
We believe that architecture is the path to unleashing information potential. One device. Or every device. One business or a value chain. One nation or a global economy. And of course, one person, population, or movement. Our mission is to proliferate that architecture and deliver the industry’s most robust information platform.
Let’s Put Potential to Work. Together.
Hi everyone! Thanks for joining us for part three of three of this conversation. In this segment, Rick and I will talk about the Internet of Things. In the last part of our conversation we covered how quickly data is being generated. You can find Part 1 and Part 2 of this conversation on my Perspectives author page.
MB: If you think about the latest topic everyone has been talking about is the Internet of Things, and everything connected to the Internet. Let’s talk about what you think will happen from the machine side. In one example GE talks about their jet engines – a terabyte per day just from a single engine and the kind of the optimization and productivity that can come from that type of data control and insight if you will.
RS: There are a couple stories that relate to the Internet of Things. One that’s fascinating is a company in Boston called Ginger I/O that has come up with technology that can predict two days before you get depressed that you’re going to get depressed. When I first heard about this I was pretty skeptical. I met with the head of the company and he explained to me that each of us has a standard pattern of behavior related to travel and activity and two days before any of us show any outward signs of depression your smart phone can detect a change in your normal pattern.
For example determines that your normal radius of travel begins to shrink, the number of emails and tweets that you send goes down and the amount of time you spend at home goes up etc. He told us that people with diabetes have a high correlation of depression and when you get depressed you often have a high correlation of not taking your medicine. And the consequences of not taking your insulin if you have diabetes can be very severe. So people with diabetes are actually installing this program now on their own smartphones and they are setting up an alert that tells their doctor, their kids, their neighbor, their friends just to please check in on them.
Another story about two MIT computer scientists John Guttag and Collin Stultz who created a computer model to analyze formerly discarded EKG data of heart attack patients. By sifting through the massive quantities of data and identifying patterns that lead to greater heart attack risk, they’ve created a model that has the potential to significantly improve today’s risk-screening techniques, which misidentify roughly 70 percent of patients likely to have a repeat heart attack.
MB: Very interesting. So we use the term information potential to relate to all of the things that can happen after a bunch of data is gathered or sourced from somewhere to make it better, make it more ready to make great decisions, to get it to folks at the right time. So when you think about the potential of information in terms of the world what would be the one thing that you would bet on in achieving information potential?
RS: There’s so many examples, but there are a couple that I love because I think they’re unexpected. There is one company called ESRI that does very high resolution satellite mapping that government and cities use for understanding and visualizing cities. ESRI that there were villages in Nigeria that didn’t exist on any map, no one knew these people were there. The Nigerian government simply didn’t have any record that these people existed. The reason this was particularly important was that the Gates foundation was working with the Nigerian government to try to eradicate polio. Nigeria is one of the countries in the world that polio has made a major resurgence. By overlapping the satellite imagery with data coming from the 10,000 GPS enabled cell phones provided by Gates to the inoculation workers they are now able to map in real-time where these workers have been to make sure that every single family is inoculated. You wouldn’t think of using satellite data to eradicate polio in remote places in the developing world.
And look at the Google car where the vehicle is able to navigate at high speed utilizing existing data about the road and incorporating real time information including radar being bounced off the pavement so the car can “see” what’s happening three cars ahead.
MB: We’re really looking forward to seeing you in June for Informatica World. I think what you’ll see at the conference is another 2,000 people with 10,000 stories on how big data is going to change the world one small company or large company at a time. So, thanks so much for your time and we’re really looking forward to seeing you.
RS: Thank you, I can’t wait.
Thanks for your interest in this conversation between Rick and myself. We hope to see you next week in Las Vegas for Informatica World 2013!