From DevOps to… MarketOps?

A recent global survey by Teradata probed the minds of marketers:

• 50% of markets say marketing and IT are not strategic partners
• 40% of marketers gave their department a grade of C or lower for using data to drive marketing
• 71% of marketers plan to implement a Big Data analytics solution in the next two years

While there is much more information in the report, these insights into marketers and their dissatisfaction with their IT brethren are reminiscent of a similar problem that was addressed by the DevOps movement.

Several years ago, the DevOps movement emerged in direct response to a similar lack of partnership, in this case between developers and IT. Developers, driven to use agile methods to sustain the pace of innovation, were often at odds with IT staff members driven to formalize and implement IT and corporate governance. New technologies meant business plans and capital expenditures. But with the advent of virtualization and cloud technologies, IT staff finally had license and a new set of tools to rapidly provision resources to support agile development. IT staff could simultaneously maintain governance through virtual machine catalogues and centralized metering, monitoring and administration. The movement also kicked off a level of IT automation, with tools such as puppet, chef and Amazon’s cloud formation, to name a few, that enabled developer and IT agility at scale. While there is still much work to do, DevOps has racked up its share of successes, with full IT support, and now is headed in the right direction.

With that short background, the statistics posted in the beginning of this post are more easily understood. More or less concurrent to the DevOps movement was the start of the Big Data phenomenon. The generally accepted attributes of Big Data (volume, velocity, variety and complexity) accentuated a DevOps-like problem — only now marketers are added into the fray along with all that big ugly data – and DevOps look like the rigid party.

When marketing asks for correlations between social media and an ad campaign or, when they ask to mine all the emails that are in salesforce so they can find out what  customers are really saying, DevOps is challenged. That’s because the tight coupling between business logic and the underlying relational data models require up-front schema design before data ingesting. Following ingestion is a process of continual cleansing, transformation and synchronization before application development can commence. Relational models are notoriously rigid. Any change requests or new data sources from marketing create ripple effects across the ENTIRE application stack and the processes it supports. This system is fundamentally brittle, inflexible and incapable of supporting the agility required for addressing today’s dynamic markets.

Change in the form of data velocity, variety, volume and complexity are fundamental attributes in the world of Big Data. Marketers seek to capitalize on the dynamics of Big Data for operational efficiency, customer intimacy and new product opportunities, while maintaining data compliance standards. These strategic goals require a level of agility not achievable when underlying data models are relational and such a tight coupling exists between the model and the services it provides to the application layer.

It should be clear that a new approach, based on Enterprise NoSQL and semantic technologies, is needed to remove impediments to marketing, development and IT partnership and agility. This new approach is characterized as follows:

• Load data as-is

  • No sorting, selecting and transforming to fit a pre-defined schema
  • Ingest CMS & DAM systems, often having > 300-500 elements
  • Allow users to find what they are looking for by capturing ALL data
  • Facilitate merging different system with different taxonomies
  • Easier to make information available across data layer
  • Allow to work directly with the raw data for speed

• Search and Discover

  • Leverage integrated, powerful search engine
  • Figure out how to interact with data, then build applications

• Build applications with an agile suite of app services

  • Developers can quickly and easily build apps that run on MarkLogic
  • Use semantics to find new opportunities
  • Use semantics to maintain compliance and enhance fraud detection
  • Reduce time to develop web or mobile apps (6-8 weeks)
  • Increase agility with semantic relations that decouple app services from data model

Whether it’s called “Marketing-Ops,” “MarketOps,” or “DevOps X.0” is not important. What is important, and apparent, is that a new approach is required to tackle the challenges of Big Data so that enterprises can benefit from the tremendous insights it offers – and so that there can be that kumbaya moment between marketers, developers and IT.