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2024 DataIQ 100

Patrick Atallah, Chief Data Officer, NXP Semiconductors

Describe your career to date

 

I started my career at Sprint International in London; I remember my first job was to train executives on how to use Sprint’s email SW application. I then spent 18 years in the telecom industry, mainly in sales and general management roles in Europe. I mostly worked for US companies, developing private data network solutions for global banks and pharma companies. When voice services were deregulated, I moved into building up European consumer consumption of voice networks. 

 

With the consolidation into that industry, I took the opportunity to shift to audiovisual, where over the last six years I have developed the first digital transformation of the audiovisual rights holders domain, via a unique number ISAN (ISO). This allows authors, producers, broadcasters, and major media companies to register their media assets into a central registry. It is accessible via web services, reducing the rights calculation from an average of two years to almost real time, and cuts costs dramatically. 

 

This is where I realised that at the heart of digital transformation was data. Because of this, I have built my own consultancy serving large corporations in Europe and the Middle East. Along the way I have also built a digital marketing agency, with marketing analytics as our key value proposition. I sold my consultancy in 2015 and joined DSM in early 2016. Initially, I was in charge of digital transformation, then for five years led their data analytics globally – from strategy to execution (data engineering, scientists, management, business intelligence), as well as digital innovation with data science for new business models.

Patrick Atallah.jpg

Data literacy is a key enabler of the value and impact from data. How are you approaching this within your organisation?

 

Data literacy is being tackled at different levels within NXP:

  • For the data professionals (within IT, data teams, and most importantly within data domains) via a community of practice, an example being data scientists, data stewards, and data engineers sharing best practices. This enables everyone to speak the same language and to organise the same way across the organisation;
  • Via a citizen movement. Data science is what we have started with, with more than 250 citizen data scientists in the past three years from all domains;
  • With our data analytics academy, we have combined three different initiatives into one. Delivering data training to employees in the domains (sales, manufacturing, supply chain, etc.) on our different platform;
  • Via content available on SharePoint, to understand what artificial intelligence (AI) and generative AI is, the policy, etc;
  • Via Yammer posts, bringing topics like why we need a data strategy, or about data mesh into everyone’s language;
  • We also recently started exposing the executive committee to generative AI use cases and different types of large language models. This was mainly on three aspects: where we need to focus to capture the value, what does it mean for our way of working (transformation), and lastly how do we need to upskill, reskill, and hire the right talents.
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