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FWD Group - Insurer Innovation Award 2024
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Effective data discovery is crucial for maintaining compliance and mitigating risks in today's rapidly evolving privacy landscape. However, traditional manual approaches often struggle to keep pace with the growing volume and complexity of data. Join us for an insightful webinar where industry leaders from TrustArc and Privya will share their expertise on leveraging AI-powered solutions to revolutionize data discovery. You'll learn how to: - Effortlessly maintain a comprehensive, up-to-date data inventory - Harness code scanning insights to gain complete visibility into data flows leveraging the advantages of code scanning over DB scanning - Simplify compliance by leveraging Privya's integration with TrustArc - Implement proven strategies to mitigate third-party risks Our panel of experts will discuss real-world case studies and share practical strategies for overcoming common data discovery challenges. They'll also explore the latest trends and innovations in AI-driven data management, and how these technologies can help organizations stay ahead of the curve in an ever-changing privacy landscape.
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
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Modern Trends in IT
1.
By Crishantha Nanayakkara Head Of Technology, ICTA @crishantha (Twitter) Global Trends in Information Technology
2.
Platform 1.0Platform 1.0Platform 1.0Platform 1.0 Platform 2.0Platform 2.0Platform 2.0Platform 2.0 Platform 3.0Platform 3.0Platform 3.0Platform 3.0 (1980s to 1990s) (2000
- 2010) (2010 onwards)
3.
Platform 1.0Platform 1.0Platform 1.0Platform 1.0 ● Centralized processing platform ● The MainFrame era ● IBM domination ● Hardware companies dominated ● Still there are platform 1.0 implementations
4.
Platform 2.0Platform 2.0Platform 2.0Platform 2.0 ● Distributed processing platform ● Rapid improvement in low cost computers / servers ● Invention of TCP/IP and the Internet ● Middleware, Messaging Systems, App Servers, Web Servers, etc ● Software only companies started to grow
5.
The Layered Architecture
6.
MiddlewareMiddleware Enterprise Application Enterprise Application Enterprise
Application Enterprise Application Enterprise ApplicationEnterprise Application Enterprise Application
7.
7 SOA Source: Open Source
SOA
8.
SOA
9.
Platform 2.0 IssuesPlatform 2.0 IssuesPlatform 2.0 IssuesPlatform 2.0 Issues ● Platform 2.0 infrastructure was not able to handle the scalability aspect for the increased growth in demand for the services ● Social media pushed to store more unstructured data than the structured data, which traditional databases could not handle ● With the heavy load of data, the demand for a real time analytical systems were needed
10.
Platform 3.0Platform 3.0Platform 3.0Platform 3.0 ● Processing Data in the Cloud (Cloud Computing) ● Integrate mobile devices with the enterprise APIs ● Incorporate new sources of data to the Internet of things (IoT) ● Manage and share data that has high volume (Big Data) ● Turn the data into usable information through analytics (Big Data Analytics) ● Ability to build software cheaply and fast, deploy it instantly (DevOps) - The Modern Generation
11.
Cloud ComputingCloud Computing
12.
12 ● Built on the Virtualization concept ● Virtualization Software creates virtual servers with pooled resources ●
It is easy.. – To create virtual servers – To provide resources on demand – To manage – To self provision – To meter / bill the usage
13.
13
14.
14 Source: http://www.zdnet.com/article/what-is-docker-and-why-is-it-so-darn-popular/
15.
15 Traditional HW Model vs Cloud Model
16.
16 The Deployment Models Public Cloud Private Cloud Hybrid Cloud
17.
17 The Deployment Models
18.
18 The Service Models IaaS (Infrastructure As A Service) PaaS (Platform
As A Service) SaaS (Software As A Service) Amazon EC2 GoGrid WSO2 Stratos CloudFoundry Windows Azure Amazon EC2 GoGrid Rackspace Joyent SalesForce Network Architects Application Developers End Users
19.
19
20.
Application Program Interfaces (APIs)Application Program Interfaces (APIs)
21.
● An API is a set of programming instructions and standards for accessing a Webbased software application or Web tool. ● A software company releases its API to the public so that other software developers can design products that are powered by its service. ● Mobile applications are heavily using these lightweight APIs
22.
Source: http://www.programmableweb.com/news/who-belongs-to-api-billionaires-club
23.
23
24.
25.
Open DataOpen Data
26.
Open Data
27.
28.
29.
Big DataBig Data
30.
● Facebook is one of big data's biggest champions, and it claims to operate the largest single Big Data clusters anywhere, with more than 100 petabytes of disk space ● The site stores more than 250 billion photos, with 350 million new ones uploaded every day ● Uses Hadoop, Hive and Hbase as the core technologies in the back end
31.
A new generation of technologies and architectures, designed to economically extract VALUE from very large VOLUMES of a wide variety of data by enabling high VELOCITY capture, discovery, and/or analysis.
32.
The Three Vs of Big Data ● Volume – Big ● Variety – From different sources and types ● Velocity – Frequency of its generation: how quickly the data arrives and is stored, and how quickly it can be retrieved
33.
The Three Vs of Big Data
34.
The Digital Universe ● From 2005 to 2020, the digital universe will grow from 130 exabytes to 40,000 exabytes, or 40 trillion gigabytes.
35.
According to IDC, the Big Data technology and service market was about US$4.8 billion in 2011. The market is projected to grow at a compound annual growth rate (CAGR) of 37.2% between 2011 and 2015. By 2015, the market size is expected to be US$16.9 billion. [Source: IDC. Worldwide Big Data Technology and Services 20122015 Forecast.]
36.
Gartner reported that more than 65 billion devices were connected to the internet by 2010. By 2020, this number will go up to 230 billion [Source: https://www.gartner.com/doc/1799626]
37.
● Over a history that spans more than 30 years, SQL database servers have traditionally held gigabytes of information — and reaching that milestone took a long time. ● In the past 15 years, data warehouses and enterprise analytics expanded these volumes to terabytes. ● And in the last 5 years, the distributed file systems that store Big Data now routinely house petabytes of information. The Statistics
38.
p Reference: Hadoop In Action Hadoop Architecture
39.
HDFS
40.
Hadoop Eco System
41.
NoSQL
42.
Internet Of ThingsInternet Of Things (IOT)(IOT) The next mega era in Computing
43.
IoT is a
network of uniquely identifiable endpoints/objects that communicate using IP connectivity without human interaction. Here, all the objects will be “online” and ready to serve you automatically. (World Wide IOT Taxonomy, 2015 IDC)
44.
45.
46.
AT&T Digital Life
Tablet App
47.
● A number of important technology changes have coincided to enable the rise of the IOT, – including cheap sensors, – inexpensive bandwidth, –
cheap processing, – smart phones, – wireless coverage, – big data, – opensource technology, – IPv6
48.
● The worldwide IoT market will grow from $655.8 billion in 2014 to $1.7 trillion in 2020 (IDC). ● Today 43% of world wide IoT revenue comes from manufacturing, transportation and smart cities ● Within next 5 years all industries should come up with a business plan for an IoT initiative
49.
● By 2018, 60% of IT solutions will be “Open Sourced” allowing IoT markets to form Because Open Sourced products are – Open – No vendor locking –
Better Community based development, which is good for complex systems like IoT – Most Big Data options are open source.
50.
Thank YouThank You
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