The Festival of Technology | Tech Bhubaneswar

Authored by S. Ravi, Technology Advisor

Tech Bhubaneswar an annual technology conference organized by Mindfire Solutions in Bhubaneswar, Odisha is a much sought after event. It  gives working professionals the opportunity to hone their technical knowledge, network and collaborate with other professionals as well as industry experts.

This year I had the opportunity to attend and speak at the fourth edition of this conference aptly titled ‘4.0.’ You can read about my sessions here.

I had the privilege to meet, interact and learn the opinions of many industry experts in the field of Blockchain & Machine Learning.

Here are a few key sessions of interest:

The Keynote session titled AI: Discover the Power of Artificial Neural Networks (ANN) which was given by Girish R Nuli. In this session Girish explained how modeling machines use the concept of neural networks by building artificial neural networks, and opens use cases that are simply not possible with deterministic programming techniques. He explained the workings of Artificial Neural Networks , the various types used in different use cases, and where the technology is heading into the future.

The next sessions, titled AI Enabled Document Extraction was given by Prajnajit Mohanty. In this session Prajnajit spoke about the approach of extracting information from financial documents such as Invoice/AP/AR/credit notes/statements etc. and different format such as pdf, images, word, excel etc. using Deep Learning and RPA in universally accepted formats like JSON. Mohanty also described  current challenges in the data/info extraction including handwritten docs etc. and the approaches adopted by leaders in the space such as Google/MS/AWS.

Sriyank Siddhartha presented the next session, Firebase on Android: The Big Picture, explaining the foundational knowledge of why and when to use Google Firebase in Android applications. Talking of how he uses core Firebase functionalities to develop and maintain high-quality apps, he further explained how to leverage its (Firebase) powers to improve apps quality while in production and to grow business. He also spoke how to integrate Firebase in an Android application. His session was quite informative and he gave a clear picture of why and when to use Firebase to develop as well as maintain high-quality apps.

I presented on ‘Full Stack Web Development Without JavaScript’, for those of you who do not know, we at Infogain held a meet up on Single Page Application, and you can read about it here. I spoke about the challenges faced by architects and business owners while choosing technologies for full-stack web application development and how those challenges can be addressed by Blazor, a new SPA framework by Microsoft. You can read more about my sessions here.

‘Making sense of emerging technologies together’ the second keynote of the day and by far one the most engaging ones. Presented by Ritesh Modi, who spoke about emerging technology trends and how to bring together all emerging technologies to create intelligent and modern solutions, in addition to how developer/solution providers can be successful using them. He also gave a hands-on demo creating an intelligent application using cognitive services deployed in Kubernetes environment using DevOps CI/CD pipelines.

In addition to technology sessions, there were a few startup and career development sessions such as  “Opportunity Potential Score” by Deepak Chaudhury, a personal transformation coach, where he spoke about ideas, innovation and shared his mathematical model to help people identify the next game changing ideas and disruptions.

Overall, the sessions were very informative and gave the audience opportunities to interact with experts in the fields of web development, Blockchain, AI & ML.

 

Reviewing the Basics of Robotic Process Automation

Robotic Process Automation (RPA) is a type of business process automation software that deploys robots to automate manual, repetitive tasks. RPA allows anyone to define a set of instructions for a robot or ‘bot’ to perform. RPA bots are capable of mimicking most human-computer interactions to complete a vast number of error-free tasks at high volume and speed. In simple terms, Robotic Process Automation frees employees to focus on more interesting and challenging human centered work.

RPA has proven its ability to deliver meaningful results and is leading to an era of Intelligent Automation through the integration of AI/ML. Some real-world examples and calculations of hours are saved with Infogain’s Intelligent Robotic Process Automation, including:

  • PO Processing: 1300 hours per year manual effort reduction
  • Report creation and distribution: 3800 + hours saved per year
  • Monthly revenue reconciliation process: Reduction of 800 hours per year
  • Foreign exchange rate adjustments: 80% reduction of manual efforts
  • Month end close: Reduction of the process from 6-7 days to 8 hours
  • Purchase requisition workflow: Yearly saving of 14,000 manual hours per year

RPA technology provides significant benefits for organizations, including:

  • Lower cost of operations with cost savings of 25-30%
  • Enhanced precision and improved productivity by up to 80%
  • Uninterrupted business flow with non-intrusive, disruption-free RPA integration and implementation
  • Automated processes that minimize manpower dependency
  • Accelerated business value creation

Infogain delivers the expertise, tools, and frameworks to accelerate the digitalization process with RPA. Our holistic approach to automation includes end-to-end methodologies, process selection, ROI measurement, vendor recommendations, reusable automation frameworks, training kits, and launch plans.

Contact an Infogain RPA specialist here.

Case Study: Infogain deploys and integrates the RPA platform to Google Cloud, providing a robust platform for cognitive and on-demand automation. Read more here.

Infogain Achieves Automation Anywhere’s Gold Partner Accreditation

Los Gatos, CA, October 16, 2019: Infogain, a leading provider of technology solutions, is pleased to announce that it has been accredited as a Gold Partner by Automation Anywhere, a leader in Robotic Process Automation (RPA). The Gold Partner recognition underscores Infogain’s role as an industry-led engineering company and a full-service automation provider.

Infogain has transformed clients’ businesses by implementing innovative and integrated automation solutions ranging from RPA programs to enterprise-wide cognitive transformations on leading industry platforms. Infogain has pioneered Automation Anywhere implementations for complex transformation scenarios where the company has combined deep software engineering expertise, digital consulting with functional domain to deliver tangible business outcomes for clients.

Infogain has been acknowledged as one of the first partners to deploy and integrate Automation Anywhere on Google Cloud and AI platform for a world leading digital hospitality marketplace, unveiling the company’s success story at the Google Next’19.  Infogain’s solution included intelligent bots integrated with Google’s AutoML Vision Object Detection products on Google Cloud to automate content curation and creation across documents and images.

“We are excited about the interest we have seen, particularly in building out RPA Centers of Excellence and the use of artificial intelligence and machine learning to scale cognitive automation,” said Gans Subramanian, VP & Global Head of Digital Experience and Insights at Infogain. “Achieving accreditation, Gold Partner by Automation Anywhere allows us to deepen and extend our relationships with clients and bring the power of Automation Anywhere’s investment in cognitive bots to our customer’s digital transformation journeys.”

“Intelligent automation enables organizations to achieve greater efficiency eliminating mundane and repetitive tasks, in turn creating a shift in human focus to top priorities and key initiatives,” said Nitin Brahmankar, Vice President of Partnerships & Alliances, North America at Automation Anywhere. “Companies like Infogain offer a full spectrum of automation services with enterprise integrations, making them a fundamental partner to help clients achieve operational success and improved productivity.”

Infogain’s Intelligent Automation Solution offerings include Robotic Process Automation (RPA), Service Automation, Data Automation and Cognitive Automation. The automation practice consists of highly trained and certified developers, including analysts, process experts, modelers, architects, developers and data analysts. The team has worked on digital transformation and automation initiatives in technology, retail, travel, and insurance industries. Infogain has developed Rapid Assessment and Deployment kits for RPA fitment and adoption, reusable DevOps based automation framework across the entire bot lifecycle.

About Infogain

Infogain is a Silicon Valley headquartered company with expertise in software platform engineering and deep domain skills in travel, retail, insurance and high technology. We accelerate the delivery of digital customer engagement systems using digital technologies such as cloud, microservices, robotic process automation and artificial intelligence for our clients. For more information, visit www.infogain.com.

 

For more information, contact:

Infogain
Cathy Chandhok
Chief Marketing Officer
cathy.chandhok@infogain.com
(408) 355-6028
Archetype
Gaurav Dhawan
Account Director
gaurav.dhawan@archetype.co
+91 9911508885

 

Architecting the Data Management Platform Success Story

Authored by Deepak Kushwaha, Program Manager

The Data Management Platform (DMP) can be visualized as a data warehouse. DMP is a software that houses audience and campaign data from various kinds of information sources. DMPs talk to demand side platforms (DSPs) and help marketers unify audience and performance data across different sources. Get introduced  to DMP by reading our blog, ‘An Introduction to Data Management Platform (DMP)’.

According to a report by Digital Journal, the DMP market is expected to grow at 15% CAGR growth and reach USD $3 billion by the year 2023. DMPs have use cases that span industries that include eCommerce, Auto, Retail, Real Estate, Travel and Hospitality, and Financial products. With extensive use cases the DMP should see a 100% adoption rate, however, despite various off-the-shelf solutions in the market, DMP implementations are riddled with challenges. For success, CIO’s must overcome these challenges:

Challenges:

  1. Audience performance measurability across devices and channels, including real-time and offline.
  2. Scale and effectiveness with onboarding first-party, second-party and third-party data audiences
  3. Ability to syndicate custom audiences at scale across channels, including offline
  4. Lack of complete view of consumers in platforms such as Facebook
  5. Accuracy in cross-device linkages to consistently and accurately identify consumers
  6. Audience Data Loss after Integration with DSP and Ad Serving Platform
  7. Data pixels provided by DMP are too large to be implemented in Third-Party partners

Good architecture design is the key to overcoming these challenges, when stitching together with the data from various sources that work together to develop a 360-degree view of the audiences. Here is a six-stage architecture for a custom DMP.

  1. Data Sources Identification – Identifying all the data sources is the first step. These sources can be first/second or a third party such as WebApp, Mobile App, CRM, Partner Data, SAP, Retail Transactions, Google AdWords, Social sites such as FB, etc.
  2. Data Aggregation – Data Aggregation, is the second and one the critical steps, performed by existing solutions such as Google Tag Manager or Tealium.  Only the script provided by Tag Manager (GTM/ Tealium) is used in a client’s codebase, which extracts the complete required analytics data. The Tag Manager internally configures all the other analytics tags.
  3. Data Collection and Processing – This step utilizes external systems (Kochawa, AppBoy, Google AdWords, FB Analytics, AppFlyer) for fetching and processing data. A simple way to gather cross channel/device data. Tags have specific functions and should be reviewed and selected based on requirements. These tags are applied to capture user actions data performed on the data source (website or App).
  4. The DMP – The complete set of data from step 3 is cleaned, classified, stitched, processed and analyzed before storing in the DMP. At this stage, the DMP is a data storage unit. Choosing optimum cloud storage such as S3, AWS EMR, RDS, Redshift, Apache Hadoop, Hive is imperative; and based on volume of data, performance or other nonfunctional parameters.
  5. Data Analytics – Nearly the last step, data analytics forms the base for adding machine learning algorithms (based on R/Python/SQL/Spark) for building a customer profile, look-a-alike models, segmentation and custom audiences. Offline provisions are made based on the clients’ needs and the volume of data to be made available.
  6. Dashboard/Publish Data – In the final stage, the dashboard contains all the reports.  All real-time and offline data is shown through a secure Rest API’s to another 3rd party, DSP’s, Ad service platform. Email notification services are also integrated with DMP to campaign client ads/coupons/offers to the targeted custom audience etc.

From a review of the requirements to careful selection of technology used, the role of an architect is crucial to the successful DMP implementation. DMP’s help brands gain an edge by making their data more portable and easier to integrate with DSPs. It provides a competitive advantage by leveraging millions of data profiles from consumers; performing business analytics; and creating custom segments and audiences.

Infogain helps Data Management executives and CXO’s to achieve their business objectives. We invite you to connect with us at info@infogain.com.

Infogain at Google Cloud Next’19 | Robotic Process Automation (RPA) and Google Cloud AI

Infogain’s team will be in San Francisco for Google Cloud Next’19, which brings together some of the brightest minds in tech for three days of networking, learning, and problem solving. Connect with thousands of IT professionals and executives across industries while engaging in deeper technical content, hands-on learning, and more access to Google experts than ever.

Infogain delivers value to our own and Google’s customers, by leveraging its strategic partnership with Google. The partnership allows Infogain’s enterprise customers a secure, flexible and cost-effective cloud platform. Our services include:

  • Cloud roadmap consulting
  • Workload migration
  • Cloud native application development
  • Managed support services
  • AI/ML using GCP Services
  • Automation

Visit INFOGAIN’S TEAM AT GOOGLE NEXT’19

Schedule a meeting with us at partner Automation Anywhere’s Booth S1669, in Moscone South – Lower Level

Contact us to schedule a meeting during the event.

For more information about Infogain, visit www.infogain.com.

An Introduction to Data Management Platform (DMP)

Authored by Sanjay Hooda,  Business Advisor

DMP or “data management platform” aggregates all kinds of data from various sources, including online, offline or mobile sources, by allowing users to access that data in various ways. The core idea behind a DMP is that businesses must be able to take advantage of diverse kinds of information from a variety of sources and collect that information in one central place in order to attain the business intelligence that truly benefits the enterprise.

DMP acts as a thread between a CRM, data vendors, and websites to deliver targeted content to customers and “look-alikes” around the Web.

DMP can be used for targeted advertising to customers and their look-alikes, and segment people with particular demographic or behavioral attributes. Running on the ad tech platform, DMP is to digital advertising what engines are to cars. They help forge better personalized content served on websites, emails, mobile apps and informs call center scripts. Research indicates 80% of consumers are more likely to make a purchase when brands offer personalized experiences. DMP helps companies to nurture existing customers and find new ones. According to Gartner, by the end of 2022, data management manual tasks will be reduced by 45 percent through the addition of ML and automated service-level management.

DMP can be instrumental in streamlining search campaigns by adding a layer of efficiency in several ways:

  • Optimized Messages and Bids for High Value Audience

Traditionally when launching a targeting campaign all searchers are treated equally. The performance report will not distinguish between someone who already researched the product and general search. In this instance, a DMP can help identify and approach these customers differently. With DMP, brands can bid on these high-value audiences that are rich with data – website visits, calls, queries, etc. by prioritizing the budget or creating different campaigns for different audiences.

  • Bridging the Online & Offline Segmentation

One challenge often faced when launching a search campaign is that once a prospect shows interest, there is a lack of knowledge on their offline activities. A DMP can be instrumental in the creation of campaigns that follow from website to offline experiences.

  • Adding Cross-Device Insights

When searches no longer have a single point of entry or continuity and has been spread across devices – laptops, mobile, tablets; mapping a customer buying journey can be tedious.

DMPs are handy in connecting users to their various devices, through both deterministic and probabilistic methods. This methodology is more transparent and gives advertisers control, compared to search engines that often don’t disclose which signals or methods they are using to stitch devices together.

  • One Experience Across All Channels

Search as a channel is unique, low-funnel and high-intent, making the metrics very different from other digital channels. However, all advertisers want brand cohesion, where all their search campaigns speak the same language as display and social campaigns.

When these campaigns are being managed by separate teams, each operating with a unique audience database, this can be a challenging task. DMPs simplify this challenge by ensuring that the same audience definition is used across all marketing efforts.

  • Privacy is Paramount

The recent turn of event GDPR, concerns regarding privacy are paramount, since the data is better safeguarded. DMP can help by adding an extra privacy layer and privacy controls. A DMP will ensure that your data is only yours and help your brand with the insights needed to tailor your search campaign.

DMP has a use case for all kind of businesses and industries:

Industry/Business Type DMP Use Case
eCommerce

 

Retargeting based on page depth

Time spent

Content consumed

Action taken on the site

Items added to the cart

Product value

Product sale value

Real Estate

 

Target audience in the CRM system based on email id/phone number

Collect email id of people who are filling out the form

Need to know which email ids are from our DMP

Financial Products Targeting ads based on movement in the stock market index
Travel

 

Tracking the PNR number or booking number of the conversions on an airline site
Telecom

 

People who have landed on client’s Facebook or YouTube pages

Targeting people whose plans are about to expire

Consumer Durables

 

Targeting users by appliances, which product did they add to cart etc.

Targeting people across Facebook and display who have visited the website, but not yet converted

Auto

 

Partnership with auto portals to pass on to audience (if we do direct deal with them)
B2B

 

Ability to find audiences that are similar to our current audience – HR professionals, CIO/CTO etc.
FMCG

 

Ability to target a demographic audience precisely. For example, female 25-35 accurately (DSPs also work with 70% accuracy)

How to achieve 90% accuracy by intersecting DSP targeting, third-party data & data from women oriented websites

Several data management platforms available right now:

  • Oracle BlueKai
  • Adobe
  • Lotame
  • Simpli.fi
  • Salesforce DMP
  • Synthio
  • ClicData
  • MediaMath (TerminalOne OS)
  • The Trade Desk
  • Mapp

Digital Journal has predicted 15% CAGR growth during the forecasted period and USD 3 billion by the year 2023. That statistic alone tells us that DMP may be the answer to the success of your future marketing campaigns, by helping to bridge cumbersome cornerstones. When you use data to inform and optimize search campaigns, brands can drive search campaigns that are relevant, interesting and informed.

Infogain helps Data Management executives and CXO’s to achieve business objectives. We invite you to connect with us at info@infogain.com.

The Impact of Artificial Intelligence and Machine Learning on Mobility

By Upakul Barkakaty, Global Practice Head of Mobility Solutions at Infogain

Mobility is no longer a fringe topic. Mobile devices have become an integral part of our lives. With the power and proliferation of high-end smartphones and tablets on the market, people are using laptops less for tasks which can be done through their mobility devices, including wearables, virtual voice assistants such as Alexa, Siri, and Google Assistant.

We are using mobile devices for everything from personal finance, shopping on Amazon and Flipkart to filling out timesheets and exploring company directories in the workplace.

Enterprise mobility solutions are undergoing a seismic shift as well. AI, machine learning, and data analytics are transforming mobility from a mere transactional function to take on a more strategic role in the organization.

Defining AI

“A machine with the ability to perform cognitive functions such as perceiving, learning, reasoning and solve problems are deemed to hold an artificial intelligence”

Although the idea of AI is not new, the pace of recent breakthroughs definitely is. There are three main factors fostering this acceleration:

  1. Computing Capacity: Advances are emerging beyond the current generation of central processing unit (CPUs) and Graphics processing units (GPUs). This capacity has been aggregated in high scalable data centers and is accessible through the cloud.
  2. Big Data: Huge amounts of information (images, voice, video, location, sensor information) are collected through IoT processes and can be used to train AI models.
  3. Machine Learning (ML): Algorithms have advanced significantly through the development of deep learning based on neural networks.

How is AI transforming Mobility?

AI and Apple’s A11 Bionic Chip. Apple’s iPhone X has introduced A11 Bionic chip. The chip contains a neural engine to power its AI features and applications like Face-ID recognition and Augmented Reality. How powerful is the A11 Bionic Chip?

Samsung is also at work to add AI-specific CPU cores into its mobile chips, and San Diego chipmaker Qualcomm announced its Snapdragon 845 chip, which sends AI tasks to the most suitable cores thus enhancing operations for energy-hungry features.

Use cases for AI in mobile app development 

AI-powered solutions in mobile app development are changing the organizations modeling with innovative applications and solutions.

  • Empowering Search Engines – Artificial intelligence and machine learning have introduced a new way to use images and voice, unlike text mode.
  • Artificial Intelligence Combined with the IoT – AI lets your devices communicate with each other. AI is collecting real-time data. That data is processed so that devices learn to function on their own.
  • Smartphone Camera Are Getting Better in Subject Detection – By using AI, the interface of a smartphone camera can easily detect the subject in the camera frame. Amazon is already using this function. Instead of scanning a barcode, users can simply place an order by taking a photo of an object. Similarly, there are home design applications using AI and AR.
  • High App Authentication – With AI and ML, security concerns have been reduced by giving alerts to the users about possible threats and vulnerability by analyzing the user behavior
  • Virtual Colleague Chatbot – Meet Nysa, Infogain’s virtual employee. She has answers to questions related to Infogain ecosystem 24x7x365. Nysa never asks for vacation time, she never complains about the food in the cafeteria, and most importantly, she doesn’t ask for a raise!
Machine learning, on a global scale, makes mobile platforms more user-friendly, improves the customer experience, maintains customer loyalty, and aids in building consistent omnichannel experiences.

 


Six most lucrative use cases for machine learning in your mobile app.

Use-cases in the Insurance Industry

An insurance tech startup (Lemonade) based in New York City, processes claims within three seconds with the help of an AI-powered claims settlement bot. The bot verifies details of claims, and runs them through a fraud detection algorithm and passed instructions to the bank to transfer the claim amount.

Natural Disaster Management: Early warnings of a disaster can be determined with accumulated data related to a specific geographic location using remote monitoring tools to perform analytics with AI & ML.

Health Monitoring: Patients wearing health and fitness trackers can have their vitals continuously sent to the doctors or to the smart device manufactures with the help of IoT platform. That data can be processed to create advanced smart devices and better decision making for disease cure.

AI-powered tools and insurance: Natural language processing, machine learning, chatbots, predictive analysis, marketing personalization — a lot is happening in the insurance industry, and it’s all being driven slowly by advancements in artificial intelligence. There is great potential for cost savings, product improvement, and improvements in customer experience.

Conclusion

AI, machine learning, and data analytics are transforming mobility, and their impact will continue to yield promising solutions, especially with the application of IoT.

With the impact of AI and ML on mobility, the possibilities are endless. If you’d like to learn how AI and ML can improve your mobility solutions, contact an Infogain Mobility expert here.

Infogain and Automation Anywhere Partner Joint Roundtable at Grand Hyatt, San Francisco

February 20th, 2019

Infogain & Automation Anywhere Joint Roundtable
Grand Hyatt, San Francisco
5 p.m. – 8 p.m. PST

Enterprises today are changing their operating models to ones that incorporate digitization and leverage automation. RPA has proven its ability to deliver meaningful results and is leading to an era of Intelligent Automation (through integration of AI/ML).

Learn from technology experts, industry influencers and your peers, as we:

  • Discuss – on key topics including managed services model for RPA, process transformation, scalability, enterprise adoption, and industry trends
  • Hear about your peers’ experiences – challenges and success stories
  • Learn from technology experts, industry veterans and influencers about strategies for successful implementation of RPA processes and technologies

Agenda highlights:

  • Topic for the event “Transforming Business Through Managed RPA”
  • Keynote by Gans Subramanian, Vice President, Head Digital Solutions – Infogain
  • Keynote by Manish Rai, VP of Product Marketing – Automation Anywhere
  • Moderator-led discussion and case studies
  • Networking dinner

Space is limited, register today for a seat at the table.

Infogain in association with TECHGIG joint Roundtable on February 15th 2019, The Leela, Gurgaon

Infogain and the Times Internet will host the roundtable: “Platform Engineering and what it means for business” on February 15th in Delhi.  This invite-only, closed-door event will host senior engineering practitioners and IT leaders driving technology related initiatives within their organizations in retail, FMCG, eCommerce and other industries.

The fast emerging ‘platform economy’ presents companies with a unique opportunity to disrupt the status quo and achieve operational excellence in the process. Platform Engineering has the potential to help companies find new avenues of growth and reinvent themselves. The difference between leaders and laggards will be determined by how well we use the platform economy to our advantage.

Session Agenda: 

  • The rise of the Platform Economy and what it means for businesses
  • Why incorporating “Customer Experience” is the key to ensuring Platform Engineering success
  • Innovation, Integration, Investment and Transactional – Which type of Platforms should be the focus areas?
  • How are Platforms used in managing supply chain transactions to improve its efficiency?
  • How are emerging technologies like IoT and Cloud Computing acting as a catalyst for Platform Engineering success?
  • Platform Engineering – Redefining Products in 2019: A 2019 Roadmap

 For more information, click here or email us at Events.India@infogain.com

IncubateIND: 5 Big Data Analytics Trends for 2019 – Naveen Arigapudi

An authored article by Naveen Arigapudi, that appeared in IncubateIND’s tech forum.

The promising evolution of Big Data and Analytics

Hyperscale data generated by digital connected devices and real-time Customer Experiences are driving a dramatic shift in analytics environments and driving actionable outcomes. Which technology trends should CIOs and CDOs be leveraging to boost their data driven initiatives?

Here are the Top 5 Big Data Analytics Trends in 2019 and beyond:

Augmented Analytics

Augmented analytics, an approach that automates insights using machine learning and natural-language generation, is the next wave of disruption in the data and analytics market. augmented analytics automates as many processes as possible, giving business users access to real insight and act on data quickly and accurately.

Gartner analyst Rita Sallam calls the approach “the next disruption in Analytics and BI”.By 2019, 50% of analytics queries will be generated using search, natural-language query or voice, or will be auto-generated.

Self-Serve Analytics Platforms and Citizen Data Scientists

The prevalence of data science and self-service analytics platforms such as Alteryx and Alpine Data will continue to give rise to citizen data scientists, those business users from cross-functional teams across enterprises who use data for everyday business decisions. These users can perform advanced analytics without having the skill set of a data scientist and with minimal dependency on IT. This frees up trained data scientists to be involved in more critical data analysis.

Edge Computing

Edge Computing, which allows information processing at the device or gateway level rather than within the cloud or a data center, has been a part of the technological space streaming network performance for quite a while now. McKinsey estimates that of the $500 billion in growth expected for IoT through 2020, approximately 25 percent will be directly related to edge technology. Edge computing will continue to help improve data compression and transfer in the connectivity layer of the technology stack, reducing network bandwidth and making a wider range of IoT applications possible.

Emergence of Enterprise Data Catalogs

The Enterprise Data Catalog serves as a single place for an organization to contain its assets. It’s an AI-powered data catalog that provides a machine- learning-based discovery engine to scan and catalog data assets across the enterprise—across cloud and on-premises, and big data anywhere. A recent report from Gartner, Data Catalogs Are the New Black in Data Management and Analytics finds that demand for data catalogs is soaring as organizations struggle to inventory distributed data assets to facilitate data monetization and conform to regulations.

Cognitive Technologies and AI

Cognitive technologies, a product of artificial intelligence (AI), has been evolving over decades, but the technology has improved dramatically in the last few years, especially in the areas of computer vision, natural language processing, speech recognition, and robotics.

According to research by IDC, between 2017 and 2021, global spending on AI-focused systems is expected to grow at a CAGR of 50 percent reflecting $200 billion in cumulative spending across an array of sectors including health care, retail, banking, and manufacturing.

(The author is the AVP – BI and Big Data Analytics at Infogain – a Silicon Valley headquartered company with expertise in software platform engineering and deep domain skills in travel, retail, insurance, automotive, and high technology. Infogain accelerates the delivery of digital customer engagement systems using digital technologies such as cloud, micro-services, robotic process automation, and Artificial Intelligence.)