Written by Zdenek Svoboda |
Each year, we kick the tires of quite a few analytical projects at GoodData. Fortunately, because we use the GoodData platform, many aspects of the embedded analytics delivery process are already streamlined, like allocating hardware or installing operating systems or software components. With these bases covered, we’ve found that the key difference between success and failure comes down to getting the right people on board. Here is my perspective on what skill sets you’ll need on your team if you want to successfully launch analytics in your product.
You probably already have a skilled UX designer on your team, but they’ll need to learn to take a few additional considerations into account when designing analytical workflows. One such example is understanding how to best utilize specific data visualizations. Typically, when we partner, we give your UX designers a crash-course in the thinking and design elements they’ll come across over the course of the project, so they’re ready to completely take over the embedded analytics design.
You’ll need a skilled data engineer for setting up a data pipeline that schedules background processes that:
- Collect all data from your product and additional data sources to a data warehouse (either GoodData ADS, Snowflake, or Redshift).
- Transform individual data sources to a semantic model.
- Partition data to individual customer’s workspaces.
- Set up the logical data model and base MAQL metrics that can later be reused by business analysts.
The data engineer is especially important for the initial phases of your project, when they’ll be setting up the baseline of your data pipeline. Later, once the data is flowing, a data engineer is much less critical, and the work of introducing additional data sources or data fields can usually be outsourced.
GoodData platform tools (e.g. Analytical Designer) provide unmatched ease of use and productivity when it comes to data analysis. Because of these capabilities and because the logical data model and important metrics have already been created by the data engineer, your data analysts are free to focus on completely understanding your product entities' life cycle and workflows. To help your analysts develop that understanding even further, product managers and designers can deliver relevant reports. As a result, even less experienced analysts can be successful, because there’s no need to build components from scratch.
GoodData can help
GoodData can help you start moving fast and efficiently right from the beginning. Our services team experts can cover all aspects of your analytical project delivery, and we work closely with your team so they can shadow, quickly learn, and take over in a few weeks. From there, the decision whether to own or outsource is yours.
Written by Zdenek Svoboda |