- Big themes and big challenges
- Data Markets: Lessons learnt and regulatory challenges
- Policy4Data and Data4Policy
BigDataStack provided insights on the second topic through its presentation “Lowering barriers for the adoption of big data analytics”
Data Markets and Adoption of Big Data Analytics
Big Data analytics have been successfully implemented in very different areas such as transportation, health and retail; offering valuable insights and projections for decision making as well as automatizing great part of business processes. This has been translated in higher productivity, outperforming existing human-programmed algorithms and even humans’ accuracy in some cases, while reducing operative costs.
However, this adoption is not an easy task and has not always been successful due to the big challenges big data presents. To use big data, an organization must define and properly implement multiple processes, overcoming several technical and legal challenges. For instance, collecting and storing the data is the first obstacle organizations face. Because of the enormous volume of big data, the data to be stored must be filtered in advanced; this requires finding the delicate balance between leaving out too much data and losing potentially vital information and storing too much data and overflowing resources. In addition, new laws such as the GDPR require organizations to clearly inform users which data will be stored and why, something that in many big data applications is hard to track.
Sharing the lessons learnt while defining and implementing the BigDataStack platform
Tackling these challenges requires skills which are usually not present in organizations new to big data processing and not easily found in the job market either. In particular, these challenges are significantly harder for SMEs and small organizations due to budget and skills limitations, creating an unfair disadvantage for them. As an effort to close this gap, we are currently developing BigDataStack: a platform that offers an easy definition, development and management of big data applications and services for analytics. In our previous example, BigDataStack can help developers and business analysts to firstly, store huge amounts of data in a simple and inexpensive way, and secondly, have a clear definition of the data to be stored, as well as its purpose, with the help of the process modelling framework. The talk focused on the lessons learnt while defining and implementing this platform, as well as the challenges identified for implementing big data analytics for three use cases in the maritime, retail and insurance industries. The slides are available below:
The BigDataStack has joined Policy4Data discussion panel on defining a joint policy brief, stay tuned!