Analytics has become easier. Think back to the years just before the millennium; those of us that used to go to work in an office before smartphones in the pre-podcast & pre-pandemic era that didn’t fulfil a role in data science – and hadn’t trained for a formal qualification in software engineering – would never have considered ourselves capable of performing business data analytics.
But things have changed. Data analytics has been ‘drawn down’ and delivered to a wider group of business stakeholders, not all of whom will possess any radically extended technical abilities in data science. Sometimes offered through simplified business dashboards, sometimes presented through abstracted drag-and-drop functions with minimal learning curves… and sometimes virtualized and embedded into our enterprise business applications such that data analytics becomes a core functional part of the way we all get used to an app’s functionality, the deep dive of data science-based analytics is now available to all a wider population of data users in various forms.
Tools for ‘data workers’
Alteryx works in precisely this space. Now working to extend the possibilities offered by its cloud-based software services and provide a range of new functionalities for all data workers, the company has this year delivered expanded cloud-connected platform experiences for its flagship Alteryx Designer product, which exists within the Alteryx Analytics Cloud Platform. At a time when self-service software tools (i.e. ones that can be initiated without the direct involvement of the IT department and its support offerings) are coming to the fore, Alteryx focusing on its own-branded Designer makes logical sense.
The software has also been extended to offer cloud-based Location Intelligence capabilities to bring spatial analytics to the masses – so, in simple terms, this is the ability to analyze data and know not just what happened and why it happened, but where (and often when) it happened too. Checking another box for compatibility with the realities of the multi-cloud world where businesses typically use more than one Cloud Services Provider (CSP) hyperscaler and any number of different operating systems and services, Alteryx has also engineered its flagship platform to be a unified entity that bridges data across all systems with centralized governance for faster insights.
“Whether you have data on-premises, in the cloud, or somewhere in-between, you need an enterprise-grade analytics platform to make sense of the data, automate it and use it to make data-driven decisions,” said Suresh Vittal, chief product officer, Alteryx. “Working closely with our technology ecosystem, we’ve made huge strides in Alteryx Analytics Cloud Platform innovations to deliver the intelligence our customers need to solve today’s problems and anticipate future demands,” notes Vittal, who also pointed to a 30% customer growth figure year-over-year in Q1 2023
If this is part of the bigger democratization of data analytics story, then how do these tools work in users’ hands, on the desktop, laptop tablet and smartphone? When in full marcoms-speak mode, Alteryx talks about so-called cloud-connected experiences; when the company is back in software engineering mode, its architects are working to enable its Cloud Execution for Desktop service to work with existing investments in data analytics and provide a cost-efficient way to centralize the management of computing resources in this space. At the upper user interface level, this means users are able to create a workflow on Alteryx Designer and then drive business decisions in concert and in unison.
Design – save – run in cloud
The process here is design workflow – save on the platform – run in the cloud… and that’s a good approximation for the way many enterprise software ‘solutions’ will (and indeed arguably should) run these days.
It enables users to a) build data-centric analyses, services or low-code/no-code applications inside dedicated designer tools, b) then save executable software code to a platform environment where it can be subject to governance checks, ratified for functionality, process compliance, user access priveledges and so on, before then c) being passed to its target cloud environment for its working life, which may see it scaled for growth under the auspices of the cloud itself.
“Our local market insight report used to manually take people up to a week to get done and now takes minutes,” said Cory Hubbard, VP of strategic analytics at Gregory Welteroth Advertising. “We’re excited to see Alteryx lowering the barrier to entry for spatial analytics even more by bringing Location Intelligence to the cloud and making it more approachable with an intuitive map-based interface. Anyone on my team can quickly become an expert and drive insights much faster than before.”
Safer governance, better pizza
Like a good pizza (hat doff to Papa John’s), good analytics stems from good ingredients and a key part of that provenance-proofing process is being able to establish rock-solid information governance. Alteryx says it has enhanced its enterprise-ready governance capabilities to make analytics more scalable. This is intended to enable all users to get the insights they need in the shortest possible time, but within an environment that is controlled, managed and with the lowest possible risk.
“Organizations can easily implement their environment of choice using private data handling, govern and secure data connections with new options for authentication, and better manage large deployments with plug-and-play [Alteryx-branded] Enterprise Utilities,” notes the company, in a technical product sheet.
Space & time
As we (the collective forces of the software industry) work to widen the data democratization envelope, we will need to bolt on (for want of a less aggressive and more constructive term) the full spectrum of functionalities to data analytics.
Within this realm, location intelligence is on that spectrum alongside temporal time-stamped data awareness, a meta-level understanding of the mission criticality of any given piece of data and its ability to be structured, integrated and secured. As already noted, Alteryz is bringing the geospatial element front and center with its new Location Intelligence capabilities. This means users will be able to identify patterns and trends to provide location-based insights that cannot typically be found with spreadsheets.
If we look at what’s happening here in as big-picture long-term platform-level (okay, holistic, point made) sense as possible, we can see data science and analytics going on a journey that’s similar to the way all eminently successful technologies go when they flourish and reach mass ubiquity to become a utility. This is not the point at which a technology become purely purchased on price (like a retail shopping commodity such as a microwave), this is the point of mass adoption when an IT service, practice or function becomes subsumed into the way all other aspects of related tech are also used.
Dont say data, say decision-making
If that utility progression ultimately happens in the Alteryx world, then we may stop calling it data science and data analytics one day – instead, we might just talk about the act of decision-making, because the data engine is already assumed to be inside our IT tools.
The company have be serendipitously leaning this way by highlighting its independently executed research analysis entitled ‘The Decision-Making Technologies Shaping the Future of the Enterprise’, which it says underlines the current state of decision-making across global enterprises. While confidence and accuracy were cited as playing an exceptionally important role in decision-making, this study highlighted multiple practices stalling the accurate and timely decision intelligence required to thrive.
According to the report, challenging economic times force business leaders to deliver the right answers at unimaginable speeds, but the current pace of decision-making is holding businesses back. The survey was conducted by Coleman Parkes in March and April 2023, and targeted 2,800 senior business decision-makers, IT decision-makers, data analysts, and line of business leaders about organizational decision-making.
This is making it difficult for businesses to make crucial decisions with the speed and confidence required. Alteryx highlights some 61% of respondents who felt that decisions were generally quick and efficient, but the reported times indicated otherwise. On average, operational decisions took two days, tactical decisions seven days, and strategic decisions took 20 days. Further here, a total of 55% of organizations questioned responded that data availability leads to faster decisions, yet only 24% reported using advanced decision intelligence technology and analytical tools to currently automate processes and help to make these decisions.
“It’s essential for decision-makers to deliver insights quickly and confidently,” said Alan Jacobson, chief data & analytics officer at Alteryx. “Isolated pockets of data and analytics access are currently hindering many organizations’ ability to gain clarity in a landscape of uncertainty. At Alteryx, we’ve long believed that data and analytically optimized decision-making deliver better, faster, more efficient and more confident intelligence – all unlocking the potential to capitalize on insights needed to design better experiences.”
Whether analytics has become a ubiquitous utility or not – and whether we drop the term and now just start talking about decision-making as a more digitally enriched business skill or not, we will still need human decision-makers, business strategists and people with enough ‘gut instinct’ to know how to create opportunities from scratch, without the aid of a computer.
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