My 5 trends for Analytics in 2019

1. Enterprise wide adoption of analytics

Organizations will continue to invest heavily in analytics across the enterprise and will turn their focus on re-tooling and re-platforming of data systems, favoring cloud-native platforms. The adoption of DataOps will escalate as it improves the quality and deployment speed of data analytics.

2. Top business outcomes of analytics

Business model transformation, customer experience enhancement, risk mitigation and revenue & profit maximization are the top business outcomes sponsors will be looking from analytics projects.

3. Industry-specific use cases

Different industries will prioritize analytics of specific relevance to their sectors. For example, fraud, risk and regulatory analytics in Banking & Insurance, marketing analytics in the Telecoms sector, and finance & accounting analytics in Utilities.

4. AutoML addresses Data Scientist shortage

Automated Machine Learning (AutoML) will democratize the data science function, whereby the number of citizen data scientists (data analysts who do not necessarily need science or business intelligence expertise) will surpass the volume of traditional data scientists. To a certain extent, AutoML will help to address talent scarcity.

5. Ethical usage of Machine Learning

Organizations will work towards developing a professional code of conduct framework for data scientists to promote the ethical use of data and Machine Learning/AI.