I specialize in developing digital content for B2B, IT, and law firms that enables them in generating more leads and driving revenue forward
What do Uber, Amazon, Netflix, and Starbucks have in common. They have a common thread. All these technological behemoths are data-first enterprises. Their laser sharp data-first have helped them to transform from startups to full-fledged industries which have leapfrogged many other players. Others must follow to stay in the game. Here are some data science trends that enterprises should prioritize:
1. Data as a Product
In 2019, Netflix released an annual report which stated that it has over 125 million accounts across the world and each account watches more than one billion hours of content every week. All those zeroes help the streaming giant collect a large volume of data about what its users like and don't like. Netflix uses that data to create original content for users and influence its distribution around the world. Its daily battle is to collect as much user preference as possible, do predictive analytics on it and use that information to inform decisions about streaming rights and pricing.
2. Rise of Chief Data Officers
Chief Data Officer (CDO) is a relatively new position in data science. Some companies like Capital One Financial Corp, eBay Inc., MasterCard Inc., T-Mobile US, and Netflix created this role to put someone at the helm of their data initiatives. The main responsibility of an enterprise CDO is to build up teams which can collect, manage, analyze and interpret all data within the company. In the coming days, companies will further invest in such roles.
3. Data Privacy Regulations
Currently, data privacy regulations are lagging behind the fast-paced world of big data and machine learning. The upcoming GDPR for instance, which is set to take effect on May 25th, 2018 focuses on transparency and accountability and requires companies to get opt-in consent from users before collecting and sharing personal data.
To best summarize the trends, next generation analytics and AI platforms will continue to be developed to bridge the gap between analytic insights and business drivers. Furthermore, DataOps [analytics teams operating with devops mindset] will become a norm as CIO's will have to align their analytics initiatives with the goals of the business. For example, IBM's Cloud Private initiative offers a DataOps platform on the IBM Cloud.
Finally, big data and machine learning engineers will continue to hold sway over data science teams because they can build models without having to ask the right question.
5. Industrial Internet of Things
In 2022, 75% of enterprise chief data officers predict that the biggest source of unstructured data within enterprises will be from IoT devices. This is expected to rise in 2022 because 2025 is when 50 billion IoT devices are projected to be in use across the world.
6. DataOps will Surge
With increased use of IoT, Big Data and Machine Learning, enterprises will have to ensure that their analytics initiatives are closely aligned with business goals, i.e. They will need a platform where data science and IT teams can work together. To that end, DataOps with devops-like approach will become the norm.
7. Rise of Digital Workspaces
In 2020, 90% of businesses have adopted digital workspaces which are powered by next generation analytics and AI platforms. By 2022, predictive analytics models built within these digital workspaces will start to perform better than those built outside them.
8. AI for Fraud Detection
A huge number of businesses will turn to next generation analytics/AI platforms for AI-based fraud detection in the next five years. The reason is because organizations are increasingly finding it difficult to handle the volume, velocity and variety of data required for effective fraud detection at scale.
9. AI-driven Digital Assistants
AI-driven digital assistants will be the norm in 2022. They will provide 24/7 virtual assistance to businesses by proactively sending alerts, performing relevant actions and providing relevant insights.
In conclusion, it is evident from the above trends that big data and AI have already transformed the business landscape as we know it. Businesses should take notice and start investing now to stay relevant in 2022 or risk being left behind.