Want to boost customer engagement? Invest in data integration, metadata, data governance, says Informatica
Featured
You may have heard about the Open Data Initiative. It's a collaboration between Adobe, Microsoft, and SAP, with the aim of facilitating data to be exchanged and enriched across systems, making it a renewable resource that flows into intelligent applications.
This may sound quite generic, but as a few people have pointed out, it really is all about customer data. The idea is that data will, one day, be stored centrally and be able to flow smoothly between different systems run by each of these software giants.
Also: Big Data 2018: Cloud storage becomes the de facto data lake
Today Informatica is unveiling what it calls the industry's first Data Hub Reference Architecture for Customer Engagement. ZDNet had a chat with Anil Chakravarthy, Informatica CEO, in order to figure out what this is about. Hint: think Open Data Initiative.
Data Hub Reference Architecture
Chakravarthy has been the CEO of Informatica since 2015, when the company went private. As he explained, Informatica has been repositioning and renewing its portfolio with a focus on enterprise data management in the cloud and leveraging a subscription-based business model.
Informatica has made some acquisitions, and inked deals with major cloud providers (AWS, Azure, Google), to make this happen. It also seems to have realized that in order to manage data efficiently, metadata is key, and shifted its focus accordingly. Informatica is named a leader in Gartner 2018 Magic Quadrant for Metadata Management Solutions.
Two of the companies with strategic investment in Informatica are Microsoft and Salesforce, and this is where things get interesting. Microsoft and Salesforce are competitors in CRM (and beyond), and this is something we need to keep in mind in order to interpret today's news, as well as the mobility we see in this domain.
To begin with, Informatica's Data Hub Reference Architecture is precisely this: a reference, a blueprint, not an actual product. Chakravarthy said it is product, and data model, agnostic. He went on to add that it complements the Open Data Initiative. If you think this all sounds a bit abstract, you're probably right.
Informatica announced its Data Hub Reference Architecture, a blueprint for data integration, which may help with customer data management.
To begin with, don't both the Open Data Initiative (ODI) and the Data Hub Reference Architecture (DHRA) sound generic? What is the relationship with Customer Engagement?
When asked, Chakravarthy acknowledged DHRA is indeed generic. He noted that customer data is spread around a number of channels and systems. This makes it hard to have a holistic view (Customer 360), therefore this is a domain that could benefit from data integration.
Also: It takes work to keep your data private online CNET
That, as far as we can tell, was also the thinking behind ODI. So it may help to take a step back and talk a bit about ODI, to try and figure out what this is all about. ODI is also quite abstract at this point. Its stated intention is to facilitate data exchange, which in theory sounds good. But there's very little we know about it.
Where's the "Open" in Open Data Initiative?
Presumably, in order to facilitate data exchange, some sort of common vocabulary would be needed. At this point, we do not know whether ODI members are considering this, and what they will come up with. For the record, there already are a couple of vocabularies around that define notions pertinent to customers and sales, such as schema.org and Good Relations.
As has been pointed out, what ODI really seems to be about is Microsoft and its partners taking on Salesforce. Salesforce is of course a proprietary platform, and its weight and market share gives it the benefit of defining its own data model and not having to reconcile with anyone about it. So Microsoft has brought some partners on board, and they promise to use one "open" data model among them.
While openness and standards in data are a good thing, we remain skeptical. Another proprietary data model as the alternative to the one Salesforce is using would only be good for ODI partners and their users. A really open data model on the other hand, based on existing standards and involving 3rd parties in its definition and evolution, would have more chances of being useful and seeing adoption by a wider community.
We know very little about Open Data Initiative at this point. But based on what we know, we have to wonder where exactly is the "open" part. Image: Microsoft
This, and the fact that Informatica stands between Microsoft and Salesforce, may help explain the stance it is taking with DHRA. Customer data is indeed a top priority for enterprises, and a truly open data model would facilitate data integration. DHRA does not include any data model, and Chakravarthy said Informatica's tools can both ingest and export metadata from/to a number of systems.
Also: How to build a business architecture for your big data TechRepublic
Chakravarthy mentioned that CLAIRE, Informatica's machine learning-powered platform, can ingest and inspect metadata to automate tasks such as entity and structure discovery and data recommendations. CLAIRE can also interoperate with systems such as Egeria, the evolution of Apache Atlas, which is open source and based on open data models. As for the ODI, which DHRA is meant to complement, it remains to be seen how open it will be.
But DHRA? What practical use is it going to have for the average enterprise? Do you really need yet another blueprint architecture? That's something you will have to decide for yourself. Data governance and metadata management is something we have repeatedly emphasized as having paramount importance. If DHRA can provide inspiration for organizations to move forward, then it is a welcome addition.
Photos: From facial recognition to connected toys, a trip inside the invisible big data revolution
Previous and related coverage:
There is no one role for AI or data science: this is a team effort
'How quote-to-cash works in in any ERP is not something that you can teach a data scientist in two days.'
AI: The view from the Chief Data Science Office
It's challenging to get data scientists where you need them. And if you're managing an AI project, better be prepared for handling moving targets. These are some of the results of a survey of chief data scientists and analytics officers that we recently concluded.
Knowledge graphs beyond the hype: Getting knowledge in and out of graphs and databases
What exactly are knowledge graphs, and what's with all the hype about them? Learning to tell apart hype from reality, defining different types of graphs, and picking the right tools and database for your use case is essential if you want to be like the Airbnbs, Amazons, Googles, and LinkedIns of the world.
What to do with the data? The evolution of data platforms in a post big data world
Thought leader Esteban Kolsky takes on the big question: What will data platforms look like now that big data's hype is over and big data "solutions" are at hand?