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Big Data Cartography

Big Data Cartography

Big Data CartographyIf you are like me and you are trying to find a synopsis of the recent changes in the Big Data industry in an easy to understand graphical format, well here it is. Matt Turck, Managing Director, at FirstMark Capital has revised his infographic chart that exhibits the state of the Big Data landscape. I like to think of it as Big Data cartography. If you didn’t see the last version, it’s organized by specific categories including Infrastructure, Analytics, Cross Structure Analytics, Applications, Open Source, and Data Source. He writes, “It’s been almost two years since I took a first stab at charting the booming big data ecosystem, and it’s been a period of incredible activity in the space.”

In an article written by Matt Turck called, “The state of big data in 2014 (chart),” he does a great job explaining, how the chart has changed over the last two years which gives tremendous insight on how the Big Data industry has evolved over that time period. He calls the new landscape chart “Big Data Landscape v 3.0” which is incredibility suiting considering the topic.

Below, I’ve highlighted some important concepts to give you a brief overview of the article (largely from a VC perspective), but click here if you are interested in reading the entire article.

Getting crowded: Entrepreneurs have flocked to the space, VCs have poured money into promising startups, and as a result, the market is starting to get crowded.”

”While there will be always room for great new startups, it seems that a lot of the early bets in the broader infrastructure and analytics segments have been made at this stage, and the bar for success is getting higher — which doesn’t mean that VC money will stop pouring in.”

Still early: Overall, we’re still in the early innings of this market. Over the last couple of years, some promising companies failed (for example: Drawn to Scale), a number saw early exits (for example: Precog, Prior Knowledge, Lucky Sort, Rapleaf, Nodeable, Karmasphere), and a handful saw more meaningful outcomes (for example: Infochimps, Causata, Streambase, ParAccel, Aspera, GNIP, BlueFin labs, BlueKai).”

Hype, meet reality: A few years into a period of incredible hype, is big data still a thing? While big data is becoming less press worthy, the next couple of years are going to be hugely important for this market, as corporations start moving projects from experimentation to full production. While those deployments will lead to rapidly increasing revenues for some big data vendors, they will also test whether big data can truly deliver on its promise.”

Infrastructure: Hadoop seems to have solidified its position as the cornerstone of the entire ecosystem, but there are still a number of competing distributions — this will probably need to evolve. “

“Some themes (for example, in memory or real time) continue to be top of mind; others are appearing (for example, there’s a whole new generation of data transformation/munging/wrangling tools, including Trifacta, Paxata and DataTamer).”

“Another key discussion is whether enterprise data will truly move to the cloud (public or private), and if so, how quickly. “

“Analytics: This has been a particularly active segment of the big data ecosystem in terms of startup and VC activity. From spreadsheet-type interfaces to timeline animations and 3D visualizations, startups offer all sorts of different analytical tools and interfaces, and the reality is that different customers will have different types of preferences, so there’s probably room for a number of vendors. Go-to-market strategies differ as well. Some startups focus on selling tools to data scientists, a group that is still small but growing in numbers and budget. Others adopt the opposite approach and sell automated solutions targeting business users, bypassing data scientists altogether.”

“Applications: As predicted, the action has been slowly but surely moving to the application layer of big data. The chart highlights a number of exciting startups that are fundamentally powered by big data tools and techniques (certainly not an exhaustive list). Some offer horizontal applications — for example, big data powered marketing, CRM tools, or fraud detection solutions. Others use big data in vertical-specific applications. “

Click here to get the entire analysis about the Big Data landscape by Matt Turck. Matt Turck is a partner at FirstMark Capital. He is also the organizer of Data Driven NYC, one of the main big data monthly events in the country.

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