Collaborative Analytics Part 2: How Enterprise SQL Communities Share Knowledge & Code Assets

A great team is more than the sum of its parts: some team members will have special aptitudes or skills; their levels of experience will differ. That's why collaboration among data analysts is so powerful.

Even an occasional insight shared among others can save valuable hours of work that might be otherwise wasted, looking for answers online or coding and recoding, trying to crack what seems to be a tough nut. 

Additionally, it soon becomes apparent in many teams that there are individuals that are outstanding teachers, skilled at imparting nuance within queries or different schema to others. Similarly, some people are better organizers than others, while certain types of developers or data scientists are a little less – shall we say — structured in their methods. 

Putting teams together and expecting them to produce the results that the business needs, day in and day out, can be a tall order. Surprisingly, it usually works out, one way or another. However, some ways and methods can improve the overall efficiency of technical workflows, enhancing the existing skills and abilities of data analysts regardless of skills and experience level. 

Most data analytics centers around SQL, exploiting efficient ways of sharing and pooling code and yielding game-changing differences to even the most distributed teams comprised of quite differently skilled members. Many SQL professionals use Aginity Pro to catalogue and reuse SQL code via a repository called the Active Analytics Catalog. 

In a previous post, we looked at the Aginity Pro’s ability to help SQL analysts save their work to the Catalog: queries, calculations, functions, and relationships, and then reference those entries quickly to save time often spent retyping or recursing through personal archives. 

While Aginity Pro helps individuals save time, we knew that tapping into your SQL community would yield even greater results, which is why we’re launching Aginity Premium.  Aginity Premium extends Aginity Pro by helping users collaborate more efficiently (and securely) to cut overall analysis overhead. It seamlessly interconnects teams’ work with the various schemas and silos used from sandboxed development instances through production. Cloud-based instances of Redshift, Snowflake, Hive, on-premises Neteeza, DB2 — the central Catalog provides a unified resource across all of these often-shifting technologies. (There’s even a git repository of Aginity catalogs, containing common SQL, to help users get up and running quickly on platforms they’ve not used as much here.)

Colleagues with specific skills can share knowledge in practical ways via discoverable Objects, so less-experienced team members will get up to speed faster. Similarly, when new people join the company, there’s less time wasted as individuals don’t have to pick their way through what might have been — initially at least — byzantine structures. Consistency begins to develop over time, as all parties involved in data analysis from whatever angle use the Discovery Assistant to find existing objects. Ongoing consistency in methods makes new projects faster to complete and existing work progress more smoothly. 

Consistency can sometimes imply static libraries of queries and functions, but a major plus point of Aginity Premium is that updates will cascade through the library. Reused elements, therefore, are as up to date as the latest iteration of any dependency that affects them. There’s a great deal less head-scratching over carefully crafted queries that worked last week but now appear to throw up errors. 

Decision-makers love Aginity, too. They know that the reusable assets will produce consistency in analytic outcomes for different user types. Business analysts and data scientists will be using the same data transformations and calculations, so the chances of intelligence-gathering teams coming up with insights at odds with one another should begin to disappear. Machine learning models will progress through learning phases much more quickly, too, so lower resource drain on compute will be an added bonus. 

Among all this, there is always the issue of less-experienced colleagues breaking something or corrupting work-in-progress elsewhere. Aginity Premium helps team leaders cut unintentionally thrown spanners by leveraging role-based privilege and entitlement tiers.  

The platform helps teams evolve with expertise shared and experience distributed. Individuals’ specific skills can become assets for all analysts, and the winners are both the data analysts and the business at large. If you haven’t explored the Aginity Pro platform yet, we suggest try it out, then talk to us about upgrading your collaborative efficiency with Aginity Premium. 

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