Insights Through Data

I already wrote a couple of posts on the topic of Automation of Operations using Alteryx, but I felt an update was in order, as the possibilities evolve so fast lately. I gauged some interest on the topic as well while presenting some of this content to an audience of data Analysts at Inspire 2016. Here is the video of the presentation.

As an Analyst, why should I care about Operations? In no particular order:

• I want to deliver the freshest possible data, to ensure relevance, as business evolves fast
• I want to expand my reach and cover new topics, while keeping the lights on those already proven valuable, and move on
• I want to capture and code complex dependencies in my data, only once, when I discover them. Repetitive attention to the same tasks is a waste of my beautiful mind
• I want to leverage more of the off hours processing cycles I have, by scheduling smartly

I understand that a lot of businesses don’t have their own analyst and instead outsource to a third party like understanding data, a data consultancy, to improve their operations. It definitely makes things easier; as the amount of data is just so large, it is difficult to ensure the right data is being used for financial gains while mitigating poor data. For companies that are just starting out or the ones who are yet to make the shift to the digital world, proper management of a huge database can be of high priority. Therefore, the need for data governance services for such companies is real, and a really smart way of boosting productivity. However, my company is lucky enough to have a team that analyzes and puts together data. Controlling Operations is also part of my vision for the agile Analyst, who’s on top of the whole chain of data, from the moment transactions get extracted from the source system to the moment analysis is consumed and interpreted by the largest audience of stakeholders. The Analyst can henceforth become confidently accountable for data integrity, as he can intervene at each step of the processing, between Alteryx and her publishing tool(s) of choice (Tableau, Power BI, Qlik, …).

Operations is a process traditionally covered by IT departments, right? Operations, which consist in automating a ad hoc analysis into a repeatable process that can be scheduled and monitored for data integrity, is definitely a more technical than business endeavour. IT managers spend so much time using resources such as time series analysis to ensure the data collected is relevant and helpful for the business to continue day-to-day operations. Yet, Alteryx makes it palatable enough for a non coding Analyst to run operations with minimal dependencies on IT, beyond the initial setup of servers and credentials. IT resource can then be allocated on more technical topics, with the analysts and their endless list of tickets off their back! This constitutes perhaps the next frontier attained by the Self Service Analytics revolution? Let’s shine some light on the options already available to Analysts…

Like for many things, Operations require decisions along a trade off: Resiliency vs. Efficiency.

Efficiency involves complexity and dependencies, Resiliency involves simplicity and robustness. I see those choices as the fun vs. effort side of a game of tug of war. Alteryx offers a variety of options from Resiliency to Efficiency, and you can pick the most appropriate to serve your business needs, mix and match, evolve along the way at your pace, just like I do as I keep discovering new ways to automate. I will group those options from Resilient to Efficient this way:

1. Simple Independent Schedules
2. Normalized Sequential Workflows
3. Scalable and Fast Complex Operations with a buffer Database

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