A SCIENTIFIC DATA SERVICES LANDSCAPE VISION
To remain competitive, we always require more robust and more effective solutions which manage the data, to facilitate and accelerate scientific discoveries as well as promote other benefits such as reduced costs. It is within a context of new analysis techniques and methods which are opening new fields of research. Within Zifo, we embrace a culture of curiosity and innovation which drives us to take up the challenge to work with our customers to explore these new opportunities.
“Data is the New Oil” is a commonly stated phrase. Perhaps we should re-phrase this as “Data is the new Renewable Energy” as the allusion to fossil fuels could mean data is finite, while data is constantly evolving and renewing. There is an overwhelming growth of public and private data being constantly developed in both quantity and quality. Our industry is more frequently emerging onto many more journeys with Artificial Intelligence (AI) and Machine Learning (ML). We help our customers by allowing them to use established algorithmic methods already used globally to solve similar problems.
Whilst both concepts – AI and ML have been discussed for decades; it is the rapid expansion of available data. Together with advances in computing power and data storage which mean we can now realise innovation in real-world scientific challenges. Zifo’s history of embracing new technologies, understanding, and managing scientific data together with our scientific knowledge means we are well prepared to meet the needs of our customers across the scientific spectrum in Pharma, Oil and Gas, Food, and Chemicals.
Within the pharmaceutical, biotech and chemical industries, we have many sources of data: some internal and some external. With outsourcing, partner networks, and a continually moving landscape as compounds and companies are purchased and divested, the sources of data become fluid and interconnected. Zifo comes with a strong knowledge in many of these areas, having delivered services and solutions for over ten years in this market.
The challenge for companies now is not only to make effective use of data but to make this capability scalable. To realise the full potential, Data Science needs to be applied consistently across the enterprise. It is not sustainable to have a Data Science strategy based on a small group of superheroes. While this will prove concepts, it fails to realise the potential and deliver continued value. The management, operation, and governance requirements all need to be considered from the beginning. There is also a further challenge in the form of change management. How to demonstrate success and engage our organisations, so everyone embraces the opportunities that Data Science offers?
Most companies in research-led sectors are investing in the delivery of data-driven strategies. They are embarking on a marathon of Data Science and Artificial Intelligence projects, hoping to gain the benefits of new technologies and data. Zifo’s experience helps companies identify successful Data Science initiatives, including AI and ML, to assist in the change management process to ensure effective and scalable deployment.
In summary, we discussed our vision of Data Science and our capabilities to deliver AI/ML for your business. In the next article, we will provide an in-depth look at machine learning and deep learning and how you can incorporate these methods into your projects.
To find out more about how Zifo can help with AI, ML, Deep Learning and scientific Data Sciences, please email us at email@example.com