ICYMI: How SPAR International uses Trifacta to manage their data

How SPAR uses Trifacta to maintain their profits and competitiveness.

3 years ago   •   2 min read

By Angelique Tzanakakis

If you thought saying goodbye 2020 meant saying goodbye to webinars, you, my friend, were wrong. It looks like webinars are here to stay.

Recently, Big Data LDN hosted a session about how SPAR International utilises Trifacta’s data wrangling platform to manage their data. If you weren’t able to attend, you can watch it here. For your convenience, I will give you a brief rundown.

SPAR is a multinational supermarket franchise with more than 13 000 locations in 48 countries. Their goal for 2020 (pre- and post-pandemic) was to ensure that they remained the largest trading supermarket chain in the world. To do this, they would need to build SPAR as a global brand to work together and put their customers first.

Tom Rose, head of operations at SPAR International, detailed the impact the pandemic had on their business. These included the increase and decrease sales of certain products, staff shortages, distribution and product availability issues, as well as unexpected additional costs on distribution.

Rose stated that they were able to glean insights and share knowledge from their locations in China and Italy - who were affected by the pandemic first - to better prepare their other location. One of their main goals, according to Rose, was to ensure stores had the right products at the right time. Thus, the insight gained from the international data played a big part in their ability to react and support customers quickly.

This is where Trifacta came into play. SPAR supported its profitable growth by utilising Trifacta to enable early access to reliable data. Rose went on to explain the challenges faced by SPAR. Some of which are the 28 different currencies, different naming conventions as well as different suppliers for the same product.

Once we had a basic understanding of their problem, Dharshini Bhuvaneswari, business data analyst at SPAR, showed us how they managed it. Bhuvaneswari explained that they needed to capture, wrangle and standardise their data. After which, they would prepare the data for specific applications.

She explained that Trifacta was able to prepare and merge different datasets once they were standardised. SPAR translated text using API through Trifacta to ensure that the underlying data was in English. Trifacta also enabled easy currency conversion.

If data isn’t your thing or your business doesn’t have a high data skill level, don’t worry. Rose acknowledged that when they were initially looking for software, they didn’t have the skills either. But with Trifacta, you don’t need an in-depth understanding to create valuable insights (although a data science background does speed things up).

You can watch the full webinar here for more details and see Trifacta in action. For more information about Trifacta, you can visit our website or read our blog post.

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