Success Stories
5 min read

How do we share our ‘know-how’ with clients? Knowledge sharing workshop with CCC

One of the foremost activities contained in the GetInData DNA is knowledge sharing. We are not just talking about knowledge sharing inside the organization but also transfer knowledge  to our clients during projects. This has become an important business practice at GetInData. Our knowledge sharing attitude includes regular meetings with product demos, workshops and training  with the customer as well as using shared JIRA, git repository and documentation e.g. Confluence and Google Docs. This helps our customers to efficiently use, own and maintain the solution we build together.  

Workshops are also one of the ways we start cooperation with clients. We organize them to understand the clients needs better, to discuss their current architecture and what we can do to build or improve it. During this kind of meeting, we also have the chance to exchange knowledge and experience in many areas in implementing Big Data technologies. Recently, our specialists were invited by CCC to support them in their data-driven transformations through knowledge-sharing workshops.

CCC S.A. is one of the largest European companies in the footwear sector. The Group has approx. 90 e-commerce platforms and 950 stores in 28 countries under the CCC, eobuwie.pl, Modivo and DeeZee brands.

CCC workshop: Data Science project approach

We organized a workshop with CCC to talk about AI / ML & cloud and the methodology of creating Data Science solutions. The main goal was to exchange knowledge, experience and inspire each other. The main speakers from GetInData were Adrian Dembek - Data Science Practice Lead and Piotr Chaberski - Senior Data Scientist, who, based on the use cases that we had to deal with, discussed the problems faced by modern Data Science teams.

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What was the workshop theme?

The main topics were ‘Development of an algorithm of customer identification among anonymous users visiting a client's website’. Development and productionization of machine learning models predicting propensity-to-buy scores for a set of products in the e-shop. Sales forecasting model for e-commerce based on offer attractiveness evaluation, seasonalities of web traffic, holidays, planned promotional activities etc. MLOps supported a pipeline with multiple Machine Learning algorithms to solve a product recommendation use case in e-commerce, based on offline and online transactional data, product images and detailed descriptions. Basket (affinity) analysis based on cash register receipts (retail, pharmacy) and a discount optimization tool for one of the biggest drug store chains.

CYTATY

The workshop audience was Data Engineers, Data Scientists and business representatives. A very positive aspect of the meeting was the fact that the majority of the Data Science team was female. This is further irrefutable proof that despite the stereotypes circulating in the IT industry, the Polish Big Data community is not only characterized by great professionalism, but also by diversity and equality.

End-to-end data landscape

From the very beginning, we were lucky to not only advise a number of scale-up and enterprise clients on their data strategy, but mostly support them in the platform implementation and enabling technology advancements. Just to show you some examples:

  • for PLAY we delivered architectural guidance and navigated the project from the PoC phase to successful full scale deployment in production. As a result, PLAY is currently using a scalable, secure, extensible Data Platform that can easily be queried for analytical, business and marketing purposes in real time, with a reduced operational cost. Read more in PLAY Customer Story
  • for ING Bank we reduced data discovery time by 30%, transferred the servers’ layer to the platform as xrdp containers in 5 months, meeting the regulations of over 40 different countries' markets. You can get more insight here: ING Customer Story 

How do we do this? We have a large group of Big Data experts in our company, so we can cover the data landscape end-to-end. We work with OpenSource technologies, with top Cloud vendors such as GCP, AWS and Microsoft and 3rd party products, well-recognized in the data management area, like Snowflake, Databricks or Ververica. 

SCHEMAT

How can we start?

When starting a project with a new customer, from day 1 we want to prove that we are a good long-term partner for their Big Data journey. Workshops are one of the practices we do to exchange knowledge with clients and offer the solutions or services that suit them the most. They are a good way to deep dive into the problem and discuss the advantages and disadvantages of each idea.
We would like to thank the CCC team for interesting and full-value workshops.

Let’s exchange knowledge together! 

We would be happy to organize knowledge sharing between our teams, please reach out to us at hello@getindata.com or through the contact form.

10 October 2022

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