|By Dan Smith||
|August 16, 2012 06:00 AM EDT||
Customer engagement has long benefited from data and analytics. Knowing more about each of your customers, their attributes, preferences, behaviors and patterns, is essential to fostering meaningful engagement with them. As technologies advance, and more of people's lives are lived online, more and more data about customers is captured and made available. At face value, this is good; more data means better analytics, which means better understanding of customers and therefore more meaningful engagement. However, volumes of data measured in terabytes, petabytes, and beyond are so big they have spawned the terms "Big Data" and "Big Analytics." At this scale, there are practical considerations that must be understood to successfully reap the benefits for customer engagement. This article will explore some of these considerations and provide some suggestions on how to address them.
Customer Data Management (CDM), also known as Customer Data Integration (CDI), is foundational for a Customer Intelligence (CI) or Customer Engagement (CE) system. CDM is rooted in the principles of Master Data Management (MDM), which includes the following:
- Acquisition and ingestion of multiple, disparate sources, both online and offline, of customer and prospect data
- Change Data Capture (CDC)
- Data cleansing, parsing, and standardization
- Entity Modeling
- Entity relationship and hierarchy management
- Entity matching, identity resolution, and persistent key management for key individual, household, company/institution/location entities
- Rules-based attribute mastering, "Survivorship" or "Build the Best Record"
- Data lineage, version history, audit, aging, and expiration
It's useful to first make the distinction between attributive and behavioral data. Attributive data, often referred to as profile data, is discrete fields that describe an entity such as an individual's name, address, age, eye color, and income. Behavioral data is a series of events that describe an entity's behavior over time, such as phone calls, web page visits, and financial transactions. Admittedly, there is a slippery slope between the two; a customer's current account balance can be either an attribute or an aggregation of behavioral transactions.
MDM typically focuses on attributive data. Being based on MDM, the same is true for CDM. Personally Identifying Information (PII) such as name, email, address, phone, and username are the primary drivers behind identity resolution. Other attributes such as income, number of children, or gender are attributes that are commonly "mastered" for each of the resolved entities (individual, household, company).
Enter Big Data. As more devices are developed - and adopted - that capture and store data, huge quantities of data are generated. Big Data, by definition, is almost always event-oriented and temporal, and the subset of Big Data that is relevant to a CE system is almost always behavioral in nature (clicks, calls, downloads, purchases, emails, texts, tweets, Facebook posts). Behavioral data is critical to understanding customers (and prospects). And, understanding customers is critical for establishing meaningful and welcome engagement with them. Therefore, Big Data is, or should be, viewed as an invaluable asset to any CE system.
Further, this sort of rich, temporal behavioral data is ripe for analytics. In fact, the term Big Analytics has emerged as a result. Big Analytics can be defined as the ability to execute analytics on Big Data. However, there are some real challenges involved in executing analytics on Big Data, challenges that drive the need for specialized technologies such as Hadoop or Netezza (or both). These technologies must support Massively Parallel Processing (MPP) and, just as importantly if not more so, they must bring the analytics to the data instead of bringing the data to the analytics. Having recently completed a course for Hadoop developers (an excellent course that I highly recommend), I have a heightened appreciation for the challenges related to managing and analyzing data "at scale" and the need for specialized technologies that support Big Data and Big Analytics.
A few significant points regarding Big Analytics should be considered:
- Big Analytics allow the build of models on an entire data set, rather than just a sampling or an aggregation. My colleague, Jack McCush, explains: "When building models on a small subset and then validating them against a larger set to make sure the assumptions hold, you can miss the ability to predict rare events. And often those rare events are the ones that drive profit."
- Big Analytics allow the build of non-traditional models, for example, social graphs and influencer analytics. Several useful and inherently big sources of data such as Call Detail Records (CDRs) generated from mobile/smart phones and web clickstream data both lend themselves well to these models.
- Big Analytics can take even traditional analytics to the next level. Big Analytics allows the execution of traditional correlation and clustering models in a fraction of the time, even with billions of records and hundreds of variables. As Revolution Analytics points out in Advanced 'Big Data' Analytics with R and Hadoop, "Research suggests that a simple algorithm with a large volume of data is more accurate than a sophisticated algorithm with little data. The algorithm is not the competitive advantage; the ability to apply it to huge amounts of data-without compromising performance-generates the competitive advantage."
Big Data is great for a CE system. It paints a rich behavioral picture of customers and prospects and takes CE-enabling analytics to the next level. But what happens when this massive behavioral data is thrown at a CDM/MDM system that is optimized for attributive data? A "basketball through the garden hose" effect might occur. But this doesn't have to happen; there are ways to gracefully extend CDM to manage Big Data.
The key is data classification. Attributive, or profile, data is classified separately from behavioral data. While both contain Source Native Key (e.g., cookie-based visitor id, cell phone number, device id, account number), attributive data can be structured only. Behavioral data, on the other hand, can be structured and unstructured and contains no PII. Big Data almost always falls under the behavioral category.
Importantly, behavioral data requires different processing than attributive data. Since the processing is different, the two streams can be separated just after ingestion, like a fork in the road, with the attributive data going one way and the behavioral data going the other. This is the key to integrating Big Data into a CDM-MDM system without grinding it to a halt. To be fair, the two streams aren't completely independent. The behavioral stream will typically require two things from the attributive stream: Dimension Tables and Master ID-to-Natural Key Cross-References - both of which can be considered as reference data.
For example, the "subscriber" dimension table may be required in the Big Data world so that it can be joined to the "web clicks" table. This is done in order to aggregate web clicks by subscriber gender, which only exists in the subscriber table.
Master ID-to-Natural Key Cross-References
Master IDs are created and managed in the CDM-MDM world, but they are often needed for linkage and aggregation in the Big Data world. Shadowing cross-references that map master IDs, such as master individual id, to "source natural keys" into the Big Data world solves this problem.
The two classifications of data are separated into two streams and processed (mostly) independently. How do they come back together? One way this architecture works is that both streams, attributive and behavioral, contain a "source natural key." This is a unique identifier that relates the two streams. For example, web clickstream data typically has an IP address or a web application-managed, cookie-based visitor ID. Transactional data typically has an account number. Mobile data will have a phone number or device ID. These identifiers don't have to mean anything, per se, but are critical for stitching the two streams back together.
It's not just the dimensionalized, aggregated data that is reunited with the profile data, but also the high-value, behavioral analytics attributes (predictive scores, micro-segmentations, etc.) created courtesy of Big Analytics. The attributive data is now greatly enriched by the output of the Big Data processing stream. And, to get things really crazy, these enriched behavioral analytics profile attributes can be used as part of the next cycle of matching; similar, complex behavior patterns can help tip the scales, causing two entities to match that might not have matched otherwise. In the end, CDM-MDM and Big Data can live together harmoniously; Big Data doesn't replace CDM-MDM, but rather extends it.
"ElasticBox is an enterprise company that makes it very easy for developers and IT ops to collaborate to develop, build and deploy applications on any cloud - private, public or hybrid," stated Monish Sharma, VP of Customer Success at ElasticBox, in this SYS-CON.tv interview at DevOps Summit, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
Jan. 31, 2015 10:45 PM EST Reads: 4,328
At 15th Cloud Expo, Shrikant Pattathil, Executive Vice President at Harbinger Systems, demos a video delivery platform that helps you do interactive videos. He discusses how Harbinger is accomplishing it in the cloud world, the problems they faced and the choices they made to get around these problems.
Jan. 31, 2015 10:45 PM EST Reads: 2,767
“DevOps is really about the business. The business is under pressure today, competitively in the marketplace to respond to the expectations of the customer. The business is driving IT and the problem is that IT isn't responding fast enough," explained Mark Levy, Senior Product Marketing Manager at Serena Software, in this SYS-CON.tv interview at DevOps Summit, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
Jan. 31, 2015 10:00 PM EST Reads: 4,379
“The year of the cloud – we have no idea when it's really happening but we think it's happening now. For those technology providers like Zentera that are helping enterprises move to the cloud - it's been fun to watch," noted Mike Loftus, VP Product Management and Marketing at Zentera Systems, in this SYS-CON.tv interview at Cloud Expo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
Jan. 31, 2015 10:00 PM EST Reads: 3,887
The 3rd International Internet of @ThingsExpo, co-located with the 16th International Cloud Expo - to be held June 9-11, 2015, at the Javits Center in New York City, NY - announces that its Call for Papers is now open. The Internet of Things (IoT) is the biggest idea since the creation of the Worldwide Web more than 20 years ago.
Jan. 31, 2015 07:30 PM EST Reads: 5,376
Want to enable self-service provisioning of application environments in minutes that mirror production? Can you automatically provide rich data with code-level detail back to the developers when issues occur in production? In his session at DevOps Summit, David Tesar, Microsoft Technical Evangelist on Microsoft Azure and DevOps, will discuss how to accomplish this and more utilizing technologies such as Microsoft Azure, Visual Studio online, and Application Insights in this demo-heavy session.
Jan. 31, 2015 05:15 PM EST Reads: 4,351
Entuity®, a provider of enterprise-class network management solutions, today announced that it solidifies its position as a market leader through global enterprise customer acquisitions and a refined channel strategy. In 2014, Entuity increased new license revenues in EMEA by over 75 percent, and LATAM by over 125 percent as customers embraced Entuity for its highly automated solution and unified architecture. Entuity’s refined channel strategy focuses on even deeper strategic alignment with ke...
Jan. 31, 2015 05:00 PM EST Reads: 1,346
We are all here because we are sold on the transformative promise of The Cloud. But what good is all of this ephemeral, on-demand infrastructure if your usage doesn't actually improve the agility and speed of your business? How must Operations adapt in order to avoid stifling your Cloud initiative? In his session at DevOps Summit, Damon Edwards, co-founder and managing partner of the DTO Solutions, will highlight the successful organizational, process, and tooling patterns of high-performing c...
Jan. 31, 2015 04:15 PM EST Reads: 4,346
The 4th International DevOps Summit, co-located with16th International Cloud Expo – being held June 9-11, 2015, at the Javits Center in New York City, NY – announces that its Call for Papers is now open. Born out of proven success in agile development, cloud computing, and process automation, DevOps is a macro trend you cannot afford to miss. From showcase success stories from early adopters and web-scale businesses, DevOps is expanding to organizations of all sizes, including the world's large...
Jan. 31, 2015 03:00 PM EST Reads: 5,506
Cloud Expo 2014 TV commercials will feature @ThingsExpo, which was launched in June, 2014 at New York City's Javits Center as the largest 'Internet of Things' event in the world.
Jan. 31, 2015 03:00 PM EST Reads: 5,293
“We help people build clusters, in the classical sense of the cluster. We help people put a full stack on top of every single one of those machines. We do the full bare metal install," explained Greg Bruno, Vice President of Engineering and co-founder of StackIQ, in this SYS-CON.tv interview at 15th Cloud Expo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
Jan. 31, 2015 02:45 PM EST Reads: 4,329
In this demo at 15th Cloud Expo, John Meza, Product Engineer at Esri, showed how Esri products hook into Hadoop cluster to allow you to do spatial analysis on the spatial data within your cluster, and he demonstrated rendering from a data center with ArcGIS Pro, a new product that has a brand new rendering engine.
Jan. 31, 2015 02:30 PM EST Reads: 3,019
"Blue Box has been around for 10-11 years, and last year we launched Blue Box Cloud. We like the term 'Private Cloud as a Service' because we think that embodies what we are launching as a product - it's a managed hosted private cloud," explained Giles Frith, Vice President of Customer Operations at Blue Box, in this SYS-CON.tv interview at DevOps Summit, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
Jan. 31, 2015 02:30 PM EST Reads: 4,298
"People are a lot more knowledgeable about APIs now. There are two types of people who work with APIs - IT people who want to use APIs for something internal and the product managers who want to do something outside APIs for people to connect to them," explained Roberto Medrano, Executive Vice President at SOA Software, in this SYS-CON.tv interview at Cloud Expo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
Jan. 31, 2015 02:30 PM EST Reads: 4,630
The Software Defined Data Center (SDDC), which enables organizations to seamlessly run in a hybrid cloud model (public + private cloud), is here to stay. IDC estimates that the software-defined networking market will be valued at $3.7 billion by 2016. Security is a key component and benefit of the SDDC, and offers an opportunity to build security 'from the ground up' and weave it into the environment from day one. In his session at 16th Cloud Expo, Reuven Harrison, CTO and Co-Founder of Tufin,...
Jan. 31, 2015 02:15 PM EST Reads: 2,758
SYS-CON Media announced that Splunk, a provider of the leading software platform for real-time Operational Intelligence, has launched an ad campaign on Big Data Journal. Splunk software and cloud services enable organizations to search, monitor, analyze and visualize machine-generated big data coming from websites, applications, servers, networks, sensors and mobile devices. The ads focus on delivering ROI - how improved uptime delivered $6M in annual ROI, improving customer operations by minin...
Jan. 31, 2015 02:00 PM EST Reads: 5,992
The move in recent years to cloud computing services and architectures has added significant pace to the application development and deployment environment. When enterprise IT can spin up large computing instances in just minutes, developers can also design and deploy in small time frames that were unimaginable a few years ago. The consequent move toward lean, agile, and fast development leads to the need for the development and operations sides to work very closely together. Thus, DevOps become...
Jan. 31, 2015 02:00 PM EST Reads: 4,553
Puppet Labs on Wednesday released the DevOps Salary Report, based on salary data gathered from Puppet Labs' industry-recognized State of DevOps Report. The data confirms that market demand for DevOps skills is growing, and that DevOps engineers are among the highest paid IT practitioners today. That's because IT organizations today are grappling with how to be more agile and responsive to the business, while maintaining the stability of their infrastructure. DevOps practices, such as continuous ...
Jan. 31, 2015 02:00 PM EST Reads: 2,527
CloudBees, Inc., has announced a $23.5 million financing round, led by longtime CloudBees investor Lightspeed Venture Partners. Existing investors Matrix Partners, Verizon Ventures and Blue Cloud Ventures also participated in the round. The latest funding announcement follows earlier rounds of $4 million, $10.5 million and $10.8 million, bringing the total investment in CloudBees to just under $50 million since the company’s inception in 2010. Previous venture investment rounds were led by Ma...
Jan. 31, 2015 02:00 PM EST Reads: 1,697
“We are strong believers in the DevOps movement and our staff has been doing DevOps for large enterprise environments for a number of years. The solution that we build is intended to allow DevOps teams to do security at the speed of DevOps," explained Justin Lundy, Founder & CTO of Evident.io, in this SYS-CON.tv interview at DevOps Summit, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
Jan. 31, 2015 02:00 PM EST Reads: 3,723