Increasing Business Productivity and Value in Financial Services with Secure Big Data Architecture

Transcription

1 Increasing Business Productivity and Value in Financial Services with Secure Big Data Architecture Stefanus Natahusada, Director/Consultant

2 Agenda Financial Services Requirements Traditional approaches & challenges New approach & challenges NoSQL Category Typical Big Data(NoSQL) Deployment Securing Big Data Infrastructure Case study Summary Q&A

3 Trend in Financial Services Regulation Risk Management New Leads/ Opportunities Minimize Cost Mobility

4 Every IT Requirement is Urgent Requirements Aggregate various data Ammend applications quickly Analyze data faster Store more data Increase productivity and Reduce TCO

5 Traditional Approaches RDBMS SAN

6 Requirements & Some Challenges Data Types: Unstructured data Semi structured data Polymorphic data Volume of Data: Trillions of records Petabytes of data Millions of queries per second Development: Iterative Short development cycles New workloads RDBMS Architecture: Commodity Hardware Cloud Computing Horizontal Scaling

7 Requirement & Some Challenges Challenges: Expensive hardware and storage Schema migration Schema change takes 3 months Application specific partitioning etc Impacts: High cost Agility lost Business frustrated Slow time to market etc

8 New Approach Is there a solution? Elastic Scaling: Horizontal Scaling Economics: Commodity Servers Big Data: Large Data Volume (Volume, Variety, Velocity) Flexible Schema: Change schema faster

9 Some Challenges Data is stored across different servers Remote Data Replication Maintaining large volume of Data is not simple Data Privacy and Confidentiality Internal and External Big Data threats

10 NoSQL Category 1. Key-Value Stores Example: DB> SET mykey CloudExpo" OK DB> GET mykey CloudExpo" DB> 2. Column Stores Example:

11 NoSQL Category 3. Document Stores Example: 4. Graph Database Example: START n=node:node_auto_index(n ame="carrie-anne Moss") RETURN n

12 NoSQL Databases

13 Typical NoSQL Deployment Shard is a horizontal partition in a database. Each individual partition is referred to as a shard or database shard.

14 Why InfoSec is a necessity? $ Hello, do you recognize us? $ We re An0Nym0U5 $ We re back. $ We ll come with more friends etc

15 Cyberattack example Source:

16 Why InfoSec is a necessity? Take note about this: When a website is attacked, the results can be devastating to an organization both financially and from a brand perspective.

17 Securing Big Data Architecture There are three main areas to Secure Big Data Architecture: People Process Technology

18 People Employees are one of the most important assets in every company/organization Develop and train them Every technology is managed by people(directly or indirectly)

19 Process Security Model for Big Data Architecture:

20 Process Traffic Flow Model for Big Data Architecture:

21 Process Application layer vs Big Data layer Security: Application DB performs faster API control Lower Disk usage vs Big Data Consistent Security Policy Reporting Centralized Audit Must have Security requirements:

22 Technology Big Data components & threats info:

23 Technology Securing NoSQL Database:

24 Technology Replication & High Availability over internet:

25 Case Study

26 Important Notes: Be careful with Server Script Deployment: * Always validate and test * Review the code Authentication and Authorization are Mandatory * Firewall, IPS, Anti Malware, Anti DDoS alone are NOT sufficient * Write customized Auth code if required

27 Summary Having a secure infrastructure will affect company s reputation and minimize unnecessary disruptions Financial Services today require more productivity, value, flexibility and lower Total Cost of Ownership(TCO) NoSQL addresses the requirements as general purpose operational Database Although the sample case study is about the Financial Services, the architecture and usage are applicable to other industries. Do inform us if we could help you get started

28 Q & A

29 Thank You