Informatica Tackles the Data Side of Innovation, Digital Transformation, Big Data, and Whatever…

The nice thing about buzzwords like digital transformation, big data, and innovation is that they are infinitely malleable, imparting permission on vendors and users alike to discuss their specific challenges and opportunities in the context of something bigger than themselves. All a board needs to hear is that someone, somewhere in the company, is focused on one or more of these buzzwords, and a warm, fuzzy feeling of accomplishment replaces that hectic panic of imminent doom.

Within this context, there’s much talk about embracing new technologies, and less, unfortunately, about the human capital and buyer behavior changes that must accompany any significant transformation. Importantly, along with technology and people (more on this coming up), there’s a third leg to the transformation race that needs close attention as well: Whatever a company wants to call it, and wherever they want to take it, and no matter how much they want to accomplish, every company’s next move is going to need a dramatically different relationship to the data that underlie new and evolving business processes.

This isn’t just because the data are different, or because the use cases are different, though those are some of the important reasons why it’s not going to be business as usual on the data side. What’s more important is that the interplay between people, business, and data is changing in ways that truly make business as usual a dead end. The pending death of silos on the business process and people side, and the emergence of new business processes from the ashes of the old, tired process of yore, needs a concomitant annihilation of silos on the data management, governance, and usage side. A 20th century relationship to the data that drives the enterprise will simply grind down any attempt to move a wannabe transformational enterprise in the 21st century.

That’s the mentality that underlies Informatica’s latest announcement, and while the messaging from Informatica focuses more on the tech issues than the business issues, the company’s “Big Data Launch” earlier this month has all the earmarks of a roadmap for data in the era of digital transformation, big data, or innovation. Might as well throw IoT and mobile in there, while you’re at it. There’s something for every buzzword in Informatica’s announcement, and the conceptual thinking of business and IT around transformation will be all the more mature for paying attention to what Informatica is talking about.

Informatica’s hat trick release of updates to PowerCenter, Data Quality, and Data Integration Hub is the company’s attempt to cover the full panoply of data management, governance, quality, and usability requirements in the modern/modernizing enterprise. This something for everyone focus – if focus is indeed the word – recognizes that any given enterprise will be moving forward in multiple cadences and directions at once.

Many of the companies I’ve talked to in recent months have embarked on simultaneous consolidation and innovation projects: consolidating and rationalizing the back office while pushing innovation at the edges. This isn’t as bipolar as it sounds: innovating on top of a moribund platform is like trying to climb a mountain with a cast on your arm – it’s better to do a little healing first before attempting the next big challenge. This purging of the back office – which in most companies has some significant legacy functionality – is a necessary precondition to a massive, transformational innovation undertaking.

Meanwhile, to get the enterprise ready for transformation, IT and the line of business in many companies have joined up to pilot an innovation project – a dab of IoT, a new, hip user experience on the commercial side, some new selling tools, etc. The important factor is that these POCs are intended to set the stage for a bigger business process innovation effort that has to change IT as much as it has to change LOB processes and sensibilities.

This complex reality is matched by the complex heterogeneity and need for hybrid cloud/on premise solutions that characterize the modern enterprise today. And underlying all the complexity on the process side is an even greater complexity on the data side. Again, there’s a similar bipolar-like feel to what’s happening in the modernizing enterprise: fundamentally, there’s still a vast quantity of older transactional data that need better overall maintenance and governance. The consolidations and rationalizations in the traditional back office have huge data cleanup requirements. Let’s be honest, among the many sins of the data warehouse mess of the late 20th century was the creation of what I call the sanitary data landfill ­– a vast data garbage dump where the fill first, analyze later mentality meant that a lot of messy data and processes were tolerated on the assumption that technology would solve the inherent needle and haystack problem that stems from too much data and not enough data quality. And that was just wrong.

Meanwhile, there’s no shortage of new data heading towards the enterprise in the form of web-based customer interaction data, real time sensor data, data historians and other industrial control data, ad infinitum. Literally. The growth in the quantity of data is matched by the growth in data types and formats – and sources. Similarly, the growth in data sources is matched by the growth in destinations: smart device communications are often bi-directional, and every controller, intelligent industrial machine, smart phone or even aircraft engine is both generating terabytes of data as well as consuming the results of the analysis of those data in the form of operational changes in what the machine, phone, or aircraft engine needs to do next, often in real time and often with some serious consequences for failure.

So – getting data right today isn’t like getting data right a decade ago. The data fudging available to the non-interconnected, non-real time, non-customer centric, and largely transaction processing-focused enterprise of the past is simply not an option in the transformative enterprise. If the data aren’t right, to a level of tolerance unheard of even a decade ago, then the transformation will be for naught.

That’s why a peek under the hood at Informatica’s latest releases is a good start for any company thinking about what has to happen to data as the company moves through a transformation cycle. Using Hadoop? Informatica’s got you covered. Real-time? Check. Improved development lifecycles for rapid prototyping and agile development? Check that too. More data and business rules visualization? Yep. Support for more data sources, improved data quality, governance, compliance? Support for next-gen analytics, customer engagement, hybrid cloud? Got that covered too.

It’s a big list, and I’ll leave it to others to dissect the feature/functionality improvements and other cool new stuff in the announcement. But I will highlight one more thing that Informatica is doing that makes tremendous sense: upping the ante, and the support, for involving business analysts directly in the data side of the transformation process. This is a tall order, and much of what has to happen here is way outside Informatica’s purview: the transformation of the business analyst into someone with a much better understanding and appreciation of data. This is part of the “human capital” leg of the transformation race mentioned earlier.

Assuming that the enterprise, or some consulting firm, will help get this business analyst transformation underway, Informatica’s focus on making its tools more business analyst friendly are right on the money. Data quality is a big business analyst issue that Informatica is supporting in its new release, and anything that brings these analysts in from the cold on key issues like data governance is more than welcome. Same with data integration – while no one expects business analysts to become integration experts, allowing them to think critically and then act, or empower IT to act, on the data integration requirements of their line of business is a huge step on the road to business transformation. There is no business transformation without people transformation, and giving the business analysts tools to help them on their way is an absolutely necessary part of this process.

Informatica, with its focus on data, is in many ways on the same journey as its prospective customers: so much has changed since the early days of PowerCenter, when IT was all inside a single firewall. These latest releases show Informatica’s determination to stay ahead of a rapidly evolving curve. I think its new functionality, and the new speed it promises for the core processes it supports, are part of a recognition that, as I said before, business as usual is one-way ticket to nowhere. Getting the data side of the new business imperative right is a key part of opening up the possibilities that business transformation, big data, IoT, or any other buzzword-compliant challenge present. Business transformation without data transformation is no transformation at all.

 

 

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