Private Equity Funcast Big in Japan (Data)
Sep 27, 2013
Dive into the world of big data where hosts explore its relevance for middle-market companies. They debate whether firms are truly facing big data problems or just need better analytics. With insights on tools like Hadoop and NoSQL databases, there's a critical look at modern analytics vs. legacy systems. The discussion emphasizes starting small, utilizing accessible platforms for analytics, and reiterates that most mid-market firms benefit from practical, straightforward data approaches rather than complex solutions. Plus, enjoy some light-hearted movie talk at the end!
AI Snips
Chapters
Books
Transcript
Episode notes
When Data Becomes 'Big'
- Big data means crossing the limits of traditional database tools and needing parallel processing and new architectures.
- Hadoop and MapReduce enable parallel analytics when data volume or velocity outstrips conventional systems.
NoSQL Is About Scale And Flexibility
- NoSQL stores (document, key-value) trade relational schema for scalability and eventual consistency suited to massive, growing datasets.
- These systems fit use cases like profiles or web logs where strict immediate consistency isn't required.
Mid‑Market Usually Doesn't Need 'Big Data'
- Most lower mid-market companies ( $20–100M revenue) rarely face true big data problems and usually don't need Hadoop or NoSQL.
- Modern compute and cheap storage make sizeable analytics feasible with traditional relational setups.
