The popularity of the data lake architecture is rapidly growing. However, deriving value from the data lake, whether for data visualization, discovery of insights or advanced analytics, requires transforming data from a “mayhem” of varied raw data into shape ready for analysis.
In the middle of the data spectrum that goes from “mayhem to managed,” there’s a sweet spot that allows for experimental, ad hoc analysis, producing data artifacts that evolve into reusable assets across the entire enterprise.
Self-service data transformation can streamline the creation of data products by taking certain ad hoc analyses and elevating them to broadly used production queries and visualizations. Other ad hoc analyses can produce re-useable data byproducts, like reference data or refined log data, helping business users do subsequent analysis work without starting from scratch.
Join Gigaom Research and our sponsor Trifacta for “Between ‘mayhem’ and ‘managed’: The Self-Service Sweet Spot for Analysis in a Data Lake” a free analyst roundtable webinar on Wednesday, September, 24th, 2014 at 10:00 a.m. PT, and find out.
What will be discussed:
- How can raw data be put into a usable (and reusable) format?
- How can engineers, data scientists, and business users work through the big data lifecycle together?
- How can business users instill rigor in their analysis work without stifling discovery, insight and agility?
- How big is the self-service data transformation ecosystem and where is it going?
Who should attend:
- CIOs and CTOs
- IT management
- Line of business managers
- Business analysts
- Data scientists