Domo seems to be hottest emerging company in the visualization, BI and so-called “Business Management Platform” area. I have been seeing it at several clients recently.
According to their pitch.. “Domo is the future of business management. For all the trillions spent on technology solutions, the way we do business still feels pretty painful. Data lives everywhere. Insights arrive too slowly. Collaboration is still wildly inefficient. Until now. Domo puts the right information, at the right time, into the hands of the people that actually use it to collaborate and make decisions. And it’s transforming the way people manage business.”
Domo grabs live business data from some 300 different sources — Salesforce, NetSuite, Twitter and Facebook included — and presents the data in a live interactive dashboard that can be customized and mixed and matched in all kinds of ways.
A screenshot of is shown below (courtesy of Recode).
Given the 2 bln valuation and growing hype, I have been struggling to figure out what Domo does that Tableau Software can’t do. Domo claims to bring the business and all its data together in one intuitive platform. Doesn’t every BI and Data Visualization platform do this? Domo claims to be developed hundreds of proprietary connectors (traditional data sources and cloud based) that connect directly to any source of data across your entire organization, and bring it into one intuitive platform. Again so does everyone else.
Recode explains this in the following manner…”Domo is not just an application but a platform, which means that if there’s some specialized business app that Domo hasn’t connected to yet, you can now start building your own connections to it and bring that data in. Those individual sections of data in the shot above are called “cards,” and you can rearrange them and add new ones to your view all the time. But if you need a special card that combines a few different bits of data and which hasn’t already been built, Domo today announced a feature it calls Card Builder that lets you create your own.”
You can be the judge and jury on how novel all this is.
Notes and References
2. List of Domo Connectors
The summer of 2015 marked the release of the blockbuster Sci-fi movie, “Terminator Genisys,” which grossed a record $350 million at the box office and further popularized the notion of time travel. In addition to sequels and prequels, Hollywood has now adopted plots for movies in which the audience can choose among alternate storylines and follow them to their logical conclusion. The future, as we know it, is plural. This year in our PreReview of 2015, we once again present a few alternative scenarios for the future from our vantage point at the end of 2014.
New business models created by emerging technologies and unforeseen partnerships dominated the headlines in 2015. Trending technologies such as the Internet of Things approached half the level of big data during 2015. Trending terms in the mainstream media such as drones and Bitcoin scored high in Google trends.
Here are three headlines from 2015 that caught our attention.
FedEx launches “parcelopter” service for 50-minute delivery Read more
In Memory Data Grid (IMGD) is a data structure that is being increasingly cited as a solution to the problem of scaling big data applications. Unlike in-memory applications, IMGDs distribute only the data across RAM over multiple servers. With memory prices continuing to fall and the volume of data for an application continuing to rise, solutions based on memory are looking more attractive to manage the performance bottlenecks of applications using Big Data. Should IMGD be on your radar screen for a Big Data application?
In order to understand this and other questions on IMGDs, Carpe Datum Rx spoke to Miko Matsumura, VP of Marketing and Developer Relations at Hazelcast, who has seen recent adoption of this technology in banks, telcos and technology companies. Here is an extract from our discussion.
Why is it so important to distribute data in a data grid? Why should it be In-memory?
In the movie “Minority Report,” set in 2054, Tom Cruise plays the captain of the “PreCrime” police force, which uses “precognitive” abilities of mutants to stop crime before it happens. Silicon Valley futurists have sometimes used this reference in the context of the art of the possible with Big Data. We have another 40 years to go to see how analytics can accurately forecast future events based on human behavior. Meanwhile, imagining the future with some level of accuracy is within our reach today.
Value creation in the data economy made headlines in 2014. While Big Data continued to be the buzzword of the year in 2014, solutions that created economic impact were center stage. Trending terms such as “predictive analytics” and “advanced analytics” approached the levels of “Big Data” on Google Trends during the year. “ROI,” which was vaguely referenced in the last two years, became the most commonly used term with Big Data in 2014. Here is a cross-section of 2014 events.
Apple announces TopsyTV
This is their next-generation TV appliance that integrates social media engagement with the TV watching experience. Earlier in 2013, Apple acquired Topsy Labs, a reseller for Twitter content for $200M. This was followed by a series of less publicized acquisitions of social media data companies. Apple is characteristically tight-lipped about its plans for monetizing this product with advertising, but speculation is rife that Apple is poised to get a piece of the $600 billion that is spent on advertising today.
In a parody of Start Trek, Silicon Valley technology companies describe their business goal as “Scale, the final frontier…”. Mid-market companies, defined as those having 100-2500 employees, may indeed provide an opportunity to emerging technology vendors to scale their business. According to Techaisle, a market research firm, these 800,000 global companies spend $300B on IT and are sought after by technology vendors big and small. In the last decade, technologies such as Cloud, SAAS and Virtualization have reached scale with a large number of mid-market companies as early adopters. Intuit, Salesforce.com, NetSuite and Amazon are just a few examples of companies who have relied upon mid-market companies as a key building block for their business.
What does this mean for Big Data? To find out, Carpe Datum Rx spoke to “SMB Guru”, Anurag Agrawal, CEO of Techaisle and the former Head of Worldwide Research Operations at the Gartner Group. Techaisle recently talked to 3,300 global businesses about their Big Data adoption plans. Here is an excerpt from our discussion.
The SMB Market is considered the Holy Grail for technology vendors because it is hard to penetrate. Does your research show that mid-market companies will adopt Big Data before large enterprises do? Are they the early adopters of this technology? Read more
In an episode of Mad Men, Don Draper talks about pitching the Kodak Carousel. “Technology is a glittering lure, but there is the rare occasion when the public can be engaged on a level beyond flash, if they have a sentimental bond with the product….Nostalgia. It’s delicate but potent. Switch it on.”
Combine the storytelling prowess of Don Draper with the high-pitched vitriol of Jim Cramer and add a dose of emotional intelligence to get Gary Vaynerchuck, social media guru, best-selling author, wine librarian and marketer par excellence of the internet age. Gary Vaynerchuck rose to prominence in social media a few years ago with his video log, wine library tv which he used to grow his family wine store into a mulit-million dollar business. He currently runs VaynerMedia, a social media strategy and production company.
Gary is an avid supporter of the use of quantitative analytics in marketing. Carpe Datum Rx caught up with Gary to ask him a few questions about big data, marketing and technology adoption in the enterprise. Here are his paraphrased comments.
Is Big Data ready for the 99 per cent ?
Digital Marketing from 1999 to 2012
In his book Permission Marketing, Seth Godin referred to email marketing as “the most personal advertising medium in history”. That was 1999.
Where does email marketing stand in 2012 in the age of social media, omni-channel marketing and big data analytics? Here are some interesting data points.
Brooks Brothers is investing in tools & testing to improve the online experience – and ↑sales. In a test involving one product category page: men’s shirts. The retailer using Bazaarvoice Ratings & Reviews software, used customer reviews to sort items on the product page. Items with five ♥♥♥♥♥- the highest rating – appeared on the top of the page. The result: a 9% lift in conversions [Adobe Digital Marketing Symposium]
Are you ready to anticipate and influence your audience in a whole new way? Value migration from traditional marketing to 24×7 digital marketing is happening in leading firms. Real-time marketing and conversion is now becoming possible.
Interestingly these are more related than you think.
The Federal Reserve wants to develop a next generation Consumer Listening Platform based on social media sentiment analytics (or opinion mining) to know what people are saying and commenting about the economy.
The goal for the Fed is to better understand which way consumer confidence is trending. Microeconomics and psychology have always been interlinked. With social media, a real-time opportunity exists to monitor local, national and even global consumer psychology. And, coupled with analyzing e-commerce transactions, insightful linkage between consumer psychology and behavior (what they are spending money on and where) is possible. Read more
“The sexy job in the next ten years will be statisticians…” ‐ Hal Varian, Google
Analytics Challenge — California physicians group Heritage Provider Network Inc. is offering $3 million to any person or firm who develops the best model to predict how many days a patient is likely to spend in the hospital in a year’s time. Contestants will receive “anonymized” insurance-claims data to create their models. The goal is to reduce the number of hospital visits, by identifying patients who could benefit from services such as home nurse visits.
The need for analytics talent is growing everywhere. Analytics touches everyone in the modern world. It’s no longer on the sidelines in a support role, but instead is driving business performance and insights like never before.
Job posting analysis indicate that market demand for data scientists and analytics gurus capable of working with large real-time data sets or “big data” took a huge leap recently. The most common definition of “big data” is real-time insights drawn from large pools of data. These datasets tend to be so large that they become awkward to work with using on-hand relational database tools, or Excel.
It’s super trendy to be labeled “big data” right now – but that doesn’t mean the business trend’s not real. Take for the instance the following scenario in B2B supply chains. Coca-Cola Company is leveraging retailers’ POS data (e.g., Walmart) to build customer analytical snapshots, including mobile iPad reporting, and enable the CPFR (Collaborative Planning, Forecasting, and Replenishment) process in Supply Chain. Walmart alone accounts for $4 bln of Coca-Cola company sales.
Airlines, hotels, retail, financial services and e-commerce are industries that deal with big data. The trend is nothing new in financial services (low latency trading, complex event processing, straight thru processing) but radical in traditional industries. In trading, the value of insights depends on speed of analytics. Old data or slow analytics translate into losing money.
As data growth in business processes outpaces our ability to absorb, visualize or even process, new talent around Business Analytics will have to emerge. New roles such as Data Scientists, Analytics Savants, Quant Modelers are required in almost every corporation for converting the growing volumes of data into actionable insights.
Look at these data stats.