The artificial turf industry has undergone several significant changes in the last decade. What used to be the easiest predictor of success (volume) is now but one of the many different dimensions by which we evaluate our success. Our sales strategy is includes several elements, including but not restricted to: product, channel, region, partner and many more. This evaluation matrix is loosely defined, and coupled with the large volume of data involved - much of it dirty - and the limited data fluency within the org, we struggle to cube our sales into meaningful metrics and compare it to our high-level sales strategy.

We are seeking a team to perform a lookback of the last 10 years of sales, define the most relevant metrics, build a regional and consolidated dashboard in Power BI that is meaningful to senior business leaders with minimal analytical training.

As part of their journey to successful deliver the final deliverables, the team will need to perform these steps:

• Gain an understanding of the business
• Perform exploratory analysis to identify which business drivers are the most significant and relevant for our senior business leaders
• Identify the relevant data sets - most of which are not integrated
• Build any simplifying SQL queries if the load on Power Query is too heavy
• Perform an analysis of the dirty data & identify reasonable assumptions that are relevant to our business as placeholder data points for the dirty data
• Building a supporting dashboard with metrics on the data quality that is easy to navigate and can be drilled down so that users can know exactly which data records require cleaning, why, and what the expected result should be

Final deliverables include:

• A presentation the covers key methodology, findings and reasoning behind selection of key metrics and visualization techniques
• The exploratory analysis (10-year lookback)
• The sales dashboard in Power BI
• The data quality dashboard in Power BI

A kickoff meeting to give an overview of the business and the business problem will be done with the Director of BI/BA;

Weekly checkins with our Marketing Data Analyst;

IT support and access to our data bases as required.