The Strata Data Conference is changing and it’s changing in a good way. At the recent Strata Data Conference in New York, Mike Olson, chief strategy officer at Cloudera, which co-sponsored the event, commented that at prior events we used to talk about the “Hadoop zoo animals,” meaning the various components of the Hadoop ecosystem of which I have written previously. Following last fall’s Strata event, I observed that the conference was evolving to focus on the use of data. Advancing that evolution, this year’s event focused on a particular type of usage: artificial intelligence (AI) and machine learning. The evolution from a focus on zoo animals to a focus on business value using advanced analytics shows further maturation of the big data market.
There’s been some speculation in the market that Hadoop may be disappearing. Some of this speculation has been driven by vendors that have recently downplayed Hadoop in their marketing efforts. For example, the Strata+Hadoop World conference is now known as the Strata Data Conference. The Hadoop Summit is now known as the Dataworks Summit. In Cloudera’s S-1 filing with the SEC for its initial public offering, the term “Hadoop” appears only 14 times, while the term “machine learning” appears 83 times. So, if some of the vendors that created the market appear to be pivoting away from Hadoop, does your organization need to do something similar, or is there a role for Hadoop in your IT architecture?
The application of artificial intelligence (AI) and machine learning (ML) to business computing will have a profound impact on white collar professions. This is especially true in heavily rules-based functions such as accounting. Companies recognize the transformational potential of AI and ML, but the progression and pace of the adoption of these technologies is unclear. Some applications of AI and ML are already in use but others are a decade or more away from replacing human tasks.
Recently Hortonworks announced some significant additions to its products at the DataWorks Summit. These additions reflect the fact that the big data market continues to evolve, as I have previously written.
This is my second analyst perspective based on our IoT Benchmark Research. In the first, I discussed the business focus of IoT applications and some of the challenges organizations are facing. Now I’ll share some of the findings about technologies used in IoT applications and the impact those technologies appear to have on the success of users’ projects.