Big Data
On the frontline mission of bridging data science skills gap in Kenya
Fascinated by the phrase ‘Big Data’, he chose to tap into his own creativity and ride on the crest of emerging data technology.
Mr Timothy Oriedo began mooting with the idea of owning a data analytics lab in 2014 but finally got it registered in May 2017 and fully operational in February 2018.
“I had acquired credibility through being accredited as the pioneer Kenyan Data Scientist by the Massachusetts Institute of Technology ( MIT) and this gave me the impetus to sail my own boat,” he told Digital Business.
He founded Predictive Analytics Lab, against the backdrop of rising need of data driven business solutions in improving decision making, operations and monetization of the data.
“Guided by this three needs, we have designed tools to be able to provide impact to businesses across various industries including media, manufacturing, hospitality, telcos and technology startups,” says the Mathematics and Special Education graduate who formed a team of data science experts, developers and researchers to steer his start up to greatness.
Big Data means a massive volume of both structured and unstructured data that is so voluminous that it cannot be processed using traditional database and software techniques.
As the Fourth Industrial Revolution enters Kenya, data analytics is becoming increasingly crucial to the economy in enabling precision in modelling future trajectories and transitions from detecting and repairing to predicting and preventing. Data analytics will also inject more jobs into the market.
However, Kenya has not been training data scientists till June this year when Moringa School launched the first ever data science course. And the ramifications of this have hit Mr Oriedo.
“The awareness on data driven decision making was still low as there was no one to bring the knowledge to them. Organizations with a high level of awareness of the data skills gap are still unable to supply enough talent to meet the rising demand,” he explains.
Moreover, there is continued reliance on outsourced turnkey data analytics solutions in Kenya, especially software developed in other countries and whose algorithms have not been calibrated to our local context.
Again, foreign data analysts hired by Kenyan corporations do not understand local data sets, and are more likely to give wrong recommendations on product or image improvement
However, the tech enthusiast has been trying his best to bridge the gap since 2018, and it has paid him handsomely, through his three revenue streams – software development, training and consulting.
“I have slightly over 100 clients that I personally train. My fee ranges from Sh7,000 to Sh25,000 per session and I try not to do less than 20 private sessions a month.”
He conducts bootcamps for general knowledge, masterclasses which are two day executive series, certified programs for Digital Finance Institute, Linkedln Learning and MapR and in house training programs privately customised for organisations .
Mr Oriedo says he is ever a humbled by the number of businesses and careers he has been able to transform through the influence of data analytics consulting.
“We are East Africa’s first comprehensive one stop platform for Data Science based in Nairobi, Kenya. Our mission is to empower the next generation of business leaders and innovators in data science,” he says.
But the biggest challenge is the trepidation with which Kenyans corporates approach the data analytics subject. This is further compounded by the
lack of a law governing data protection as it leaves the country with little room for innovation and at times Mr Oriedo avoids touching sensitive client data until a data governance protocol is agreed.
“This will only be attenuated once the Data Protection Bills is ratified into law. We also have a challenge of infrastructure costs, Big Data Analytics happens on distributed computing frameworks which unfortunately are billed per minute.
“The upfront investments that we have had to make to build proof of concept for prospective clients sometimes limits our growth trajectory,” he laments.
One can become a data scientist through on the job training, self-taught skills through online courses or taking certified programs.
Mr Oriedo believes there is value in each of these options and his start up has designed interventions that tap to each of the three realms to complement the future of retooling and reskilling the workforce towards data science.
However, the future of data science and analytics in Kenya is rosy as the economy keeps demanding these skills to improve customer experience on products.
“The future is bright, the market opportunities will continue to emerge and we believe as early adopters, we have had to pay a heavier price than the later entrants. That however will not deter us from playing our part in the Fourth Industrial Revolution.”
But Kenya is East Africa’s largest economy, and more data science training institutions will be required to match the market demands in manufacturing, health, communications, transport, education, media, agriculture and finance sectors.