Why do data science projects succeed

The last few years has dawned the age of data. 

The growth of corporations’ digital operations consistently outpace that of the traditional ones. In order to enable such growth,  understanding the online marketplace, anticipating customer needs and quickly adapting to market trends became a reality only achievable only by data-centric solutions.

Billions of dollars have been invested hoping to better realize the potential of data. The law firm DLA Piper's latest global survey has found that the total investment in data centre infrastructure worldwide rose 120% last year from USD $24.4 billion to USD $53.8 billion. Though impressive this number is just a proxy that pales in comparison to the total value actually invested in all data-related initiatives.
 

CI&T together with digital business transformation

We at CI&T are at the vanguard of these endeavours. We incorporated data into our digital transformation offer eight years ago, and we have helped clients capture business value through data. Currently 600 of 7,200 CI&Ters work as data scientists, data engineers, big-data architects and digital analysis experts at our delivery centres in Europe, South America, Asia, the US and Canada.

Across industries like  Retail, Banking, Agroindustry, Healthcare and Consumer Product Goods  we have successfully delivered advanced data solutions delivering everything: from machine learning networks using real-time data streams to heuristics; and from dashboards and descriptive statistics to cloud migration and comprehensive data strategies.

These powerful stories were built in partnership with household names like Johnson & Johnson, Anheuser Busch Inbev, Nestlé, Cielo, SKY, Bradesco and Kraft Heinz and have enabled us to learn important insights on how to deliver projects that generate hundreds of millions of dollars to impact business.

5 pillars to succeed in data science projects

In our experience successful data projects are those based on the following 5 pillars that when executed simultaneously avoid common mistakes that plague attempts to stand out in the age of data.
 
1. Prowess, the technical ability to build algorithms, mathematical and statistical skills that build models integrated to vision.

2. Process, the methodical usage of agile tools to quickly develop code, create hypotheses and test them. 

3. People, which in our experience, is the trickiest pillar as getting everyone at the project engaged, educated and focused on understanding the algorithms and their implications is crucial. 

4. Platform, the infrastructure that speeds up development and delivery and that allows solutions to be built and exploited. 

5. Purpose! Successful data projects must be linked to a business burning question, connecting the data project to a real problem that once solved yields real measurable results. 

These five pillars constitute the foundation upon which not only data products can be built but also allows a digital culture flourish. One that nourishes an experimentation driven organization that continuously seeks solutions and opportunities committed to an ongoing journey of information gathering and knowledge production. This is how we believe organizations can reap the riches of this age of data.

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