28 Oct Want To Become An AI-First Company? Hire These People
Artificial intelligence doesn’t just have a bright future—it’s at the forefront of business. AI is obviously a factor in robotics, online commerce, analytics, and the management of cloud computing. Even effective talent spotting, marketing, and a host of other business applications now count on solutions with AI baked in.
If it’s happening everywhere, now or in the near future, then every organization needs familiarity with how to build a strong digital team capable of using its proprietary understanding of products and customers to do work that adds value.
Who needs to be on it? Let’s take a look at the members of a good team.
Data analysts often organize massive and heterogeneous loads of data into something AI systems can power through. Typically, they might specialize in a few areas of interest (like data from Salesforce, Firebase, or SAP), looking for ways to make digital paths of your customer base.
To do so, they might look at digital and geographic locations, like web addresses, physical store locations, or warehouse information; they’ll mix this with customer visits, the time they spend there, the location and device from which they visited, the products and services they viewed, and what they purchased.
As a rule, data analysts love a clean schema and tight, beautiful SQL code. They’re often doing the critical work of locating and cleansing data so it delivers real insights. Once they’re done, it’s time to blend the data together into a cohesive whole. Time for another role.
Data engineers get the right stuff to the right place as efficiently as possible. That means moving data quickly and effectively across the various places it’s stored. One place (such as BigQuery) will store structured data, which comes from databases. A second place (such as Cloud Storage) might have unstructured data, like images, audio files from call centers, or PDFs of invoices.
It’s an important job, because keeping and fetching data in the right way (not just the where and how of storage, but things like whether you need the information in real time or in cheaper repositories) affects what you spend. That determines how much effective AI work a team can do. Data engineers often optimize data flow with tools like Apache Beam, the open-source programming model used to create data-processing pipelines, including ETL, batch, and stream processing. Many have experience with Spark, Hadoop, and tools of the big data era. They are well versed in networking and security. Data begins to flow! Excited teammates stop by your office, waving spreadsheets with new insights. Now you need to know how those individual insights drive your business in aggregate. Enter the next role.