Big Data Predictions for 2017
Market research and advisory firm Ovum estimates the big data market will grow from $1.7 billion in 2016 to $9.4 billion by 2020. As the market grows, enterprise challenges are shifting, skills requirements are changing, and the vendor landscape is morphing. The coming year promises to be a busy one for big data pros. Here are some key predictions for big data in 2017 from industry watchers and technology players.
1-The era of ubiquitous machine learning has arrived
2-When data can’t move, bring the cloud to the data.
3-Applications, not just analytics, propel big data adoption.
4-The Internet of Things will integrate with enterprise applications.
5-Data virtualization will light up dark data.
6- Kafka looks set to be the runaway big data technology of 2017.
7-A boom in prepackaged integrated cloud data systems.
8-Cloud-based object stores become a viable alternative to Hadoop HDFS.
9-Next-generation compute architectures enable deep learning at cloud scale.
10-Hadoop security is no longer optional. Source
11-Big data becomes fast and approachable
12-Organizations leverage data lakes from the get-go to drive value
13-The convergence of IoT, cloud, and big data create new opportunities for self-service analytics.
14-Self-service data prep becomes mainstream as end users begin to shape big data
15-Self-service analytics extends to data prep
16-Analytics will be everywhere, thanks to embedded BI
17-IT becomes the data hero source
18-Artificial intelligence is back in vogue
19-Companies focus on business-driven applications to avoid data lakes from becoming swamps
20-Data agility separates winners and losers
21-Blockchain transforms select financial service applications
22-Machine learning maximizes microservices impact
23-Data scientist demand will wane