Skip to content

Posts from the ‘Managed Analytics’ Category

20
Mar

Robotic Process Automation + Analytics


“Looking to the future, the next big step will be for the very concept of the “device” to fade away. Over time, the computer itself—whatever its form factor—will be an intelligent assistant helping you through your day. We will move from mobile first to an AI first world.” — Sundar Pichai, CEO Google

RPA.png

  • A global oil and gas company has trained software robots to help provide a prompt and more efficient way of answering invoicing queries from its suppliers.
  • A large US-based media services organization taught software robots how to support first line agents in order to raise the bar for customer service.

Software agents or Robotic process automation (RPA) is becoming a mainstream topic at leading corporations. I have seen a massive uptick in corporate strategy work in this area as C-Suite execs look at new ways to do more with less.

Software robots ∼ Conversational-AI products like Apple Siri, Microsoft Cortana, IBM Watson, Google Home, Alexa, drones and driverless cars ∼ are now mainstream. What most people are not aware of is the rapidly advancing area of enterprise robots to create a “virtual FTE  workforce” and transform business processes by enabling automation of manual, rules based, back office administrative processes.

This emerging process re-engineering area is called Robotic process automation (RPA).

Machine Learning (ML) and graph processing are becoming foundations for the next wave of advanced analytics use cases. Speech recognition, image processing, language translation have gone from a demo tech to everyday use in part because of machine learning. Machine learning models, e.g., in driverless cars,  teaches itself how to discover relevant things like a stop sign with snow partially obscuring the sign.

The market opportunity of artificial intelligence has been expanding rapidly, with analyst firm IDC predicting that the worldwide content analytics, discovery and cognitive systems software market will grow from US$4.5 billion in 2014 to US$9.2 billion in 2019, with others citing these systems as catalyst to have a US$5 trillion – US$7 trillion potential economic impact by 2025.

RPA – What?

“Robotic automation refers to a style of automation where a machine, or computer, mimics a human’s action in completing rules based tasks.” – Blue Prism

RPA is the application of analytics, machine learning and rules based software to capture and interpret existing data input streams for processing a transaction, manipulating data, triggering responses and driving business process automation around enterprise applications (ERP, HRMS, SCM, SFA, CRM etc.).

RPA is not a question of “if” anymore but a question of “when.”  This is truly the next frontier of business process automation, enterprise cognitive computing, predictive analytics and machine learning. To make a prediction, you need an equation and parameters that might be involved.

Industrial robots are remaking blue-collar factory and warehouse automation by creating higher production rates and improved quality.  RPA, simple robots and complex learning robots, are revolutionizing white-collar business processes (e.g. customer service), workflow processes (e.g., order to cash), IT support processes (e.g., auditing and monitoring), and back-office work (e.g., data entry).

I strongly believe that as cognitive computing slowly but surely takes off, RPA is going to impact process outsourcers (e.g., call center agents) and labor intensive white collar jobs (e.g., compliance monitoring) in a big way over the next decade. Any company that uses labor on a large scale for general knowledge process work, where workers are performing high-volume, highly transactional process functions, will save money and time with robotic process automation software.

RPA picture

Business Impact of RPA – Where?

Read more »

22
Dec

2015 Year in “PreReview” in Technology


The summer of 2015 marked the release of the blockbuster Sci-fi movie, tEREUy1vSfuSu8LzTop3_IMG_2538“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 »

2
Jun

Apple’s HealthKit vs. Google Fit – Wellness Platforms powered by big data and analytics


mobile-applicationsGame on….I think we just witnessed a next generation leap in Healthcare Wellness (powered by Data and Predictive Analytics).  Apple jumped into the health information business on June 2 2014, launching both a new health app (Health) and a cloud-based health information platform with IOS 8 (HealthKit). This was followed by Apple Watch, (Watch launch in September 10, 2014), an intelligent health and fitness companion.

Google followed with Google Fit on June 25. Fit is a set of APIs that will allow developers to sync data across wearables and devices. Google Fit is the equivalent of Apple’s HealthKit.  Google didn’t announce an equivalent of Apple Health app.  It is expecting its ecosystem of Android partners to innovate with apps. Google also might be taking a different approach with Fit aligned with Android Wear SDK which extends the Android platform to a new generation of wearable devices.

The connected health and wearable devices market has a multitude of participants, including specialized consumer electronics companies, such as Fitbit, Garmin, Jawbone, and Misfit, and traditional health and fitness companies, such as adidas, Nike and Under Armour. In addition, many large, broad-based consumer electronics companies either compete in fitness market or adjacent markets, including LG, Microsoft, and Samsung. Read more »

10
Mar

Fan Engagement and Wearables: Disney MyMagic+


MagicBandA satisfying experience is the driver of any business’s revenue growth. Disney Theme Parks is no exception. Disney is executing a guest (and fan) personalization strategy leveraging wearables (and analytics) to track, measure and improve the overall park experience. The goal is increase sales, return visits, word of mouth recommendations, loyalty and brand engagement across channels, activities, and time.

Wearables are the next big thing.  The new crop of gadgets — mostly worn on the wrist or as eyewear — will become a “fifth screen,” after TVs, PCs, smartphones, and tablets.

Wearables are already being used to monitoring vital signs, wellness and health. Devices like Fitbit, UP, Fuelband, Gear2 track activity, sleep quality, steps taken during the day. Consumers of all sorts — fitness buffs, dieters, and the elderly — have come to rely on them to capture and aggregate biometric data.

What most people don’t understand is how powerful wearables (coupled with  analytics) can be in designing new user experiences.  Businesses thrive when they engage customers by creating a longitudinal predictive view of each customer’s behavior. To understand the wearables use cases and potential we did a deep dive into a real-world application at Disney Theme Parks.

Wearable Computing at Disney: MyMagic+

Read more »

4
Mar

Big Data Performance Anxiety and Data Grids


In Memory Data Grid (IMGD) is a data structure that is being increasingly The Gridcited 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?

Read more »

24
Feb

Security Analytics – Big Data Use Case


Another day, another data breach.  Just received another “We’re sorry you got hacked”…letter.  

This is the fifth letter I have received in the past 3 months:  Forbes.com, Target, Neiman Marcus, credit card company and a previous employer.  What is going on?

Why aren’t firms investing in beefing up their predictive ability to spot the cyber-security intrusion threats? What’s taking them so long to identify?  Why is the attack signature – sophisticated, self-concealing  malware – so difficult to spot?   Do firms need to invest in NSA PRISM type threat monitoring capabilities?

The three impediments to discovering and following up on attacks are:

  • Volume, velocity and variety – Not collecting appropriate security data
  • Immaturity and not identifying relevent event context (event correlation)
  • lack of system awareness and vulnerability awareness

Obviously… where there is pain…there is opportunity for entrepreneurs see below – data from IBM).  There is a growing focus on big data use case for security analytics after all the breaches we are seeing.  General Electric announced it had completed a deal to buy Wurldtech, a Vancouver-based cyber-security firm that protects big industrial sites like refineries and power plants from cyber attacks.

securityanalytics3

 

Here are three recent examples that I was personally affected by – Forbes,  Target, Neiman Marcus.  

Read more »

23
Dec

2014 Year in PreReview for Big Data Analytics


In the movie “Minority Report,” set in 2054,Time Travel 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.

Read more »

12
Aug

Quantified Self, Ubiquitous Self Tracking = Wearable Analytics


google_glassesThe future is here. It’s just not evenly distributed yet.”   – William Gibson

Self-tracking,  Seamless Engagement and Personal Efficiency improvement’s new frontier is Personalized Big Data and Digital Health. This is really becoming a viable idea around wearable and sensor computing and the basis for new data platform wars.

The new platforms for digital life or data driven life — that collect, aggregate and disseminate — will  cover a wide range of new User Experience  (UX) use cases and end-points… medical devices, sensor-enable wristwear, headset/glasses, tech-sensitive clothing.  All of them are going to collect a lot of data, low latency analytics, and enable  data visualization. Several new firms are entering the activity tracker market LG (Life Band Touch), Sony (the Core), Garmin (Vivofit), Glassup, Pebble, JayBird Reign etc.

Data collection is just one piece of the solution. The foundation for personalized big data is Descriptive and Predictive Analytics.  Ok…What do i next? what is the suggestion? in the form of predictive search (automated deduction or augmented reality).

How do i discover useful patterns, analyze, visualize, share, query and mobilize the collected data?  A wide range of start-ups – Cue, reQall, Donna, Tempo AI, MindMeld, Evernote, Osito, and Dark Sky – and big companies like Apple, Google, Microsoft, LG and Samsung are working on predictive apps — aimed at enabling new robo-assistants that act as personal valets, anticipating what you need before you ask for it.

DataLeverage

Read more »

14
Jul

Blessed are the Mid-Markets, for they shall Scale Big Data


Interview with SMB Guru

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 »

11
Jun

NSA PRISM – The Mother of all Big Data Projects


Prism9As a data engineer and scientist, I have been following the NSA PRISM raw intelligence mining program with great interest.  The engineering complexity, breadth and scale is simply amazing compared to say credit card analytics (Fair Issac) or marketing analytics firms like Acxiom.

Some background… PRISM – “Planning Tool for Resource Integration, Synchronization, and Management” – is a top-secret data-mining “connect-the-dots” program aimed at terrorism detection and other pattern extraction authorized by federal judges working under the Foreign Intelligence Surveillance Act (FISA).  PRISM allows the U.S. intelligence community to look for patterns across multiple gateways across a wide range of digital data sources.

PRISM is unstructured big data aggregation framework — audio and video chats, phone call records, photographs, e-mails, documents,  financial transactions and transfers, internet searches, Facebook Posts, smartphone logs and connection logs – and relevant analytics that enable analysts to extract patterns. Save and analyze all of the digital breadcrumbs people don’t even know they are creating.

The whole NSA program raises an interesting debate about “Sed quis custodiet ipsos custodes.” (“But who will watch the watchers.”) Read more »

%d bloggers like this: