Web 2.0, Analytics 3.0, Industry 4.0. A world-weary tech worker would be minded to add TotalBull 5.0 to the list. Tech industry vendors are prone to promote grand visions that on close examination turn out to be a mishmash of concepts and technologies congregating only to shift more units.
But if you look behind the hype, some have more value than others.
Informatica, a data management software company dating back to 1993, launched Data 4.0 at its ongoing CLAIREview conference, which began on 25 May, and like so many post-lockdown conferences, seems to be going on forever.
Speaking to The Register, CEO Amit Walia certainly ratcheted up the hyperbole. “Where we see the next five to 10 years is when digital transformation actually truly starts happening. It is not just modernising an application. Every enterprise is going to transform the way they launch new products and services, their operating models, how they engage with customers and transforming their business model. Customers realise that now is the time when it’s going to be data led: that is the world of Data 4.0.”
Companies cannot buy Data 4.0. It’s not a product, but rather offers companies a “framework to transform themselves,” Walia claimed.
But David Wells, IDC senior research manager for Europe, big data and AI, explained that it is the technology behind the framework that is interesting. “They’ve been working on making that a centralised metadata-driven AI platform and that is very much in line with what IDC thinks is one of the most important technology trends in analytics.”
At stake here is the ability of companies to react as they try to find their feet while economies emerge from lockdowns and struggle with the ongoing impact of COVID-19, he said. “You need all the data you can get your hands on to try and decide how you’re going to change what you’re going to do.”
Too much time spent wrangling data
The problem is the productivity of data scientists, who help organisations make sense of all the data, is going down, not up, despite a plethora of automation tools in this area. While it is a well-rehearsed quote – that they spend 80 per cent of their time gathering and wrangling data – that figure is probably now more like 90 per cent, with only 10 per cent of time spent on analysis, Wells said, because the complexity and volume of data sets are growing faster than the application of tools designed to improve productivity.
This is where the platform approach can help, IDC’s man added.
“It is the same AI platform and it is all the same integrated tooling, which has an enormous advantage in terms of managing it and expanding it and so on. Whereas other companies, especially those that expanded by acquisition, have tended to apply AI techniques for automation, as and when it is needed. They have got one set of AI doing data exploration and another set doing data quantify, for example, and that gives them a lot more baggage to carry in terms of maintenance and integration.
“Informatica has got that: a single AI platform for data which supports automation across the board. If they do the right things, it will be a great advantage to them.”
If the Data 4.0 concept, framework, or whatever is new, then the technology is not. Informatica’s Intelligence Data Platform based on its CLAIRE automation technology has been available since 2017.
But it launched an avalanche of new features in March and this week it has added to the list with a set of “cloud-native” updates. These include the ability to automate cloud mass ingestion for files and databases, and reuse existing workloads in the cloud with minimal disruption, Informatica said. It also promises to help automate data management with AI machine learning to build and tune data integration jobs and detect anomalies.
The idea is to add a whole bunch of automation features available in the same platform. That includes data quality, master data management data catalogues, data privacy and governance, CEO Walia said.
For example, in data catalogues, behind-the-scenes rules and machine learning help give business users the opportunity to “shop” for data on a simple Amazon-like UI, he added.
The problems is, as The Register has discussed already, the enterprise data platform concept is not unique to Informatica. Cloudera, Talend, SAS, Teradata, SAP, Tibco, IBM, and Dataiku all have products they describe in a similar way.
“They mean completely different things, and that’s tricky and as is usually the case in emerging markets, everybody leaps on the phrase but it means ‘what I had before, but it’s slightly better’,” IDC’s Wells said.
For example, Cloudera can put a “single sheet of glass” over all data sources that allows organisations to manage security and privacy from one place, Wells said. But the company is not so strong on governance and integration.
Bloor Research’s Philip Howard agreed the platform approach is sound. “It certainly doesn’t help when you get Teradata and Cloudera on the one hand and Talend and Informatica on the other.
“Modern IT environments are so complex that a platform-based approach makes a lot of sense. Historically, I’ve always been in favour of best-of-breed solutions, but if you’re going to start from scratch, your best approach is to start with a platform, and add specific tools where you might want something different. Building a complete data environment nowadays you’re talking about so many different tools, they might take a year to integrate. If you buy tools that are already integrated that is a much faster time to value.”
Whether companies invest in such a platform to help them adapt to the, er, new normal could come down to politics. If the IT spending is seen as a cost, it could be in for a bit of spreadsheet pruning. If, on the other hand, the top team understands the value of data, they might realise now is the time to invest. ®
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