IT leaders within large enterprises are investing heavily in cloud-based analytics technologies for obvious reasons—flexibility, time to value, access to innovation, data gravity and more. We hear the mantra use “the right tool for the right job” at nearly every cloud technology conference, with IT leaders pushing their teams to build data pipelines that utilize the tools best suited for each type of analytics workload. This often drives cost and operational efficiency. However, it remains at odds with another growing trend in the industry, providing self-service support for analysts and data scientists who want to utilize the toolset that they are already familiar with. The good news is that a few cloud analytics vendors are already addressing these considerations effectively, and far exceeding expectations of what a “cloud analytics” vendor can offer.
Let’s discuss how.
Until recently, cloud analytics vendors either offered relational database solutions or advanced analytics/machine learning solutions. Gone are the days of IT leaders investing in separate point-solutions for reporting, predictive and prescriptive analytics, and machine learning. Large enterprises should expect their cloud analytics vendor to deliver capabilities that go way beyond SQL in a powerful database. The leading solutions are providing the capabilities for:
- Data integration, with support for multiple data sets from across the entire organization. This requires streaming in from cloud data pipelines (think Kinesis and Lambda) as well as reaching out to a variety of data stores and transactional databases and joining them in a single query.
- Machine Learning, with powerful analytic functions and engines built directly into the database.
- The tools and languages that analysts and scientists in your organization already use. You should expect to be able to point your Jupiter Notebook directly at the database and run R or Python against data already in the database.
This is particularly important in the cloud, where the prevalence of streaming data pipelines and cheap, scalable storage options mean the vendors need to get on board. Fortunately, enterprises using Teradata Vantage in the cloud can already take advantage of these capabilities. This allows large enterprises to get actionable answers, faster.