Data quality your companys biggest obstacle

Data analytics is becoming increasingly scalable, sophisticated and accessible aided by cloud infrastructure, but challenges remain in data quality and building the right culture The data analytics market has evolved rapidly, applying algorithms to larger datasets on a more frequent basis by a wider group of people and practitioners. Many of the sophisticated algorithms deployed are now more than 50 years old, but the recent ubiquity of almost limitless data storage and compute power, and improved development tools, has enabled greater scale today and for the future of data analytics.Data analytics systems have advanced to apply more complex analysis in a much more responsive manner. Analytics remains all about creating insight and providing answers to important questions, which businesses can exploit to achieve improved outcomes. Contemporary systems now apply machine-learning to more diverse datasets, where the analysis is driven to a larger extent by the computer rather than the operator. The real-time arrival of new data enables insights to be discovered as soon as they occur.