Announcement List

Data Engineering and Information Management (Weekend Program )

About the program

The term of Data Engineering was coined in 1984 by IEEE after foreseeing the role of data in the design, development, management and utilization of information systems. The technical associations and institutions like IEEE, ACM, IET and many others have agreed upon the concept of data engineering and have defined it as a speciality focusing on technologies for managing large volumes of data covering conceptual modelling and database design, data models, query languages, query processing, optimisation, and indexing.

There is an ever increasing appetite of high quality and up to date information for decision making in the modern competitive and highly volatile business environment. This situation necessitates the use of flexible as well as user-friendly tools for efficiently and effectively meeting the needs of organizations. The industries and enterprises working for a couple or more years have accumulated mountains of all sorts of data and many of them face grand challenges of properly managing it for getting useful knowledge. The recent challenge in this regard is the management of big data.

Big data is high-volume, high-velocity and high-variety information asset that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. This notion has indeed brought new dimensions to the concept of data management apart from the volume and variety thereby leading to the formal field of data engineering.

Data engineering involves the designing, building and managing of the information or "big data" infrastructure. It involves developing the architecture that helps analyse and process data in the way the organization needs it.

After building the big-data infrastructure, the next major task involves the design and development of state-of-the-art information systems over it. The curriculum for information management integrates elements of management, computing, and information science to address critical social, economic, legal, and policy challenges associated with supporting information use by individuals and organizations.

Significance of the program

This program is intended to develop sound professionals with adequate skills and knowledge to meet the latest challenges of big data and information management. The compulsory and elective courses are designed to give broad-based knowledge of the field along with developing creative and analytical thinking ability. The graduates of the program will be better able to provide logical and ingenious solutions to critical problems, data analytics, data mining and enterprise resource management. This program also intends to overcome the skill deficiency in computer science/engineering graduates in the area of Information Sciences by including the relevant courses.

Eligible Candidates

The candidate should possess Bachelors of Engineering degree or Bachelors of Computer Science, or Bachelors of Business Administration or sixteen years education in Applied Mathematics or Statistics, or equivalent with first division or minimum 2.4 out of 4.0 CGPA. Additionally, the candidate shall have to pass the entrance test.

Requirement of Non-Credit Courses shall be decided by the Postgraduate Admissions Committee after considering previous academic transcripts and experience.

Market Outlook

According to a recent survey in Dec 2014 , the demand for big data expertise across a range of occupations saw significant growth over the last twelve months in USA. There was a 123.60% jump in demand for Information Technology Project Managers with big data expertise, and an 89.8% increase for Computer Systems Analysts.

On the local arena, the number of job postings for data engineers/analysts and information management are escalating on almost all job websites of Pakistan. These opportunities are being created in various sectors including Banking, Health Care, and Telecommunications. A few of the titles recently posted on a local job website include:

  1. Senior Big Data Software Engineer
  2. Business Analyst (Health Care IT)
  3. Information Security Manager
  4. Business Intelligence/Data Warehouse Consultant
  5. SQL Database Engineer‎

Compulsory Courses

  1. CS-551 Advanced Database Systems

    CS-551 Advanced Database Systems

    This compulsory course is primarily intended to augment and solidify the background of students in various aspects of database systems. As a prerequisite, the students should have a foundational knowledge in the design, development and maintenance of database systems including some hands-on experience on a customary database management system.

    After giving the necessary overview of basic concepts, the course would involve covering the advanced topics of object-oriented databases and query optimization (for centralized systems). A major part of the course involves covering major issues in distributed databases including their design, transaction management, concurrency control and distributed query optimization.

    The course also covers an introduction to advanced concepts of analytical processing, data warehousing, data mining and multimedia databases.


    A review of core database concepts – Definitions, Architecture of Database Systems, Relational Database Management Systems, Transaction Management; Object-based and Object-oriented database systems; Query Processing and Optimization; Distributed Databases – Introductory concepts; Functions and Architectures of a DDBMS; Distributed Relational Database Design; Transparencies in a DDBMS; Distributed Transaction Management; Distributed Concurrency Control; Distributed Query Optimization; Online Analytical Processing; Introduction to Data warehouses and Data Mining; Multimedia Databases.

  2. CS-552 Data Analytics

    CS-552 Data Analytics

    This course is designed to focus on the methods, algorithms, approaches and software tools being used for modern data analytics. It covers data preprocessing, representation, visualization, correlation, regression, forecasting, classification and clustering along with the software tools and languages associated with the intelligent data representation and analysis.


    Introduction, Data and Relations, Conceptual Data models, Knowledge representation techniques, Iris Data Set, Data Scales, Similarity and Dissimilarity Measures, Sampling and Quantization, Data Preprocessing, Error Types and Handling, Filtering, Transformation and Merging, Data Visualization, Principal Component Analysis, Sammon Mapping, Correlation and Causality, Chi-Square Test for Independence, Regression, estimation, Cross-Validation, Feature Selection, Forecasting, Finite State Machines, Recurrent Models, Autoregressive Models, Data Classification and Clustering, Data manipulation languages and techniques, Software for Data Analysis.

  3. CS-553 Information Systems Management

    CS-553 Information Systems Management

    To use information effectively, businesses need people who are able to leverage a strong set of skills in Information Technology while also interacting with others who may not have these same skills.

    The course focuses on the effective management and use of information and knowledge to enable informed decision making within organisations. Covers current issues and future trends in the use of information communication technology, and focuses on the challenges managers face in linking information systems with other functional business areas.


    Introduction to Information Systems; Types and strategic uses of information systems; Business Functions and Supply Chains; Transaction Processing Systems; Decision Support and Expert Systems; Business Intelligence and Knowledge Management; Ethics and Privacy; Information Security; E-Business and E-Commerce; Enterprise Resource Planning Systems; Acquiring Information Systems and Applications.

  4. CS-554 Data Security and Audit

    CS-554 Data Security and Audit

    This course mainly covers the ISO/IEC 27001 / 27002 which specifies the requirements for establishing, implementing, maintaining and continually improving an data / information security management system within the context of the organization. It also includes requirements for the assessment and treatment of information security risks tailored to the needs of the organization. The requirements set out in the course are generic and are intended to be applicable to all organizations, regardless of type, size or nature.


    Introduction, data security policy and scope, Risk assessment and Statement of Applicability, Asset management, Communications and operations management, Controls against malicious software (malware) and back-ups, Network security management and media handling, Exchanges of information, E-commerce services, E-mail, internet use and social media, Access control, Systems acquisition, development and maintenance, Cryptographic controls, Security in development and support processes, Monitoring and information security incident management, Compliance , The ISO27001 audit. Relevant cased studies.

  5. CS-555 Distributed Systems

    CS-555 Distributed Systems

    A distributed system is one in which components located at networked computers communicate and coordinate their actions only by passing messages. Modern computer system environments are essentially distributed in the sense that most of the engineering and business applications involve the remote information processing and sharing of resources ultimately leading to high performance and cost effectiveness.

    This compulsory course aims to provide an understanding of the principles on which the Internet and other distributed systems are based; their architecture, algorithms and design; and how they meet the demands of contemporary distributed applications.


    Characterization of Distributed Systems; Distributed Models; Interprocess Communication; Distributed Objects and Remote Invocation; Remote Procedure Call; Distributed Mutual Exclusion and Election algorithms; Distributed Transactions and Concurrency Control; Mobile and Ubiquitous Computing; Web Services; Security and Privacy

Elective Courses

  1. CS-561 Advanced Internet Computing

    CS-561 Advanced Internet Computing

    This course covers a broad array of technologies and concerns related to the Internet.

    Besides covering major internet applications and protocols, the course will cover the architectures, enabling technologies, software utilities, and engineering techniques that are necessary for internet and take advantage of Web-based services.


    Basics of internet computing, Transmission protocols (DNS, HTTP, POP, SMTP), Other related protocol (ICMP, BGP, ARP), Current emerging trends, 4G/5G Mobile tele-communication, IPV6, Internet programming, Android architecture and programming, Dynamic Web Development, Network Security. Information Retrieval, Web Crawling and Search, Agents, Digital Rights Management, XML Core Technologies, Introduction to Web Semantics, Web Services and Information Modeling on the Web

  2. CS-562 Big Data Computing

    CS-562 Big Data Computing

    Services like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database. As scale and complexity of data increases Big Data Computing starts to play its role.

    This course reveals big data analytics as the next wave for information technology looking for competitive advantage. Also it takes an in-depth look at the financial value of big data analytics. This course covers tools and technology and best practices for working with big data


    Introduction, Taxonomy and Review of Big Data, Challenges and Opportunities, Semantic Technologies and Big Data, Management of Big Semantic Data, Linked Data, Interoperability, Big Data Processing, Data Exploration, Data Processing with MapReduce, Efficient Processing of Stream Data, Web Ontology Languages, The Economics of Big Data, Advanced Data Analytics for Business, Big Data Applications, Big Social Data Analysis, Real-Time Big Data Processing.

  3. CS-563 Business Intelligence

    CS-563 Business Intelligence

    Business Intelligence (BI) deals with concepts and technologies capable of handling large amounts of unstructured data to identify develop and find new strategic business opportunities intelligently.

    This course outlines a methodology that takes into account the complexity of developing applications in an integrated BI environment. This include from strategic planning to the selection of new technologies and the evaluation of application releases. Starting from design then development and finally deployment of BI plan with the help of various case studies will also be a part of the course.


    Business Intelligence (BI) and Information Exploitation, Value of BI, Planning and developing the Roadmaps, BI Environment and maturity levels, Business Processes and Information Flow, Data Requirements Analysis, Metadata, Data Quality and Integration, Knowledge Discovery and Data Mining, Data Warehouses and the Technical BI Architecture, Strategic Intelligence in Corporate Planning, Tactical Intelligence in Marketing, Operational Intelligence in Manufacturing, Financial Intelligence in Accounting, High-performance BI, Emerging BI Trends, Related Case studies

  4. CS-564 Cloud Computing

    CS-564 Cloud Computing

    Cloud computing has become a significant technology trend. Experts believe cloud computing is currently reshaping information technology and the IT marketplace.

    This course will provide an overview of Cloud Computing in an enterprise environment. It will focus on fundamentals and recent trends in cloud computing along with the deployment of various cloud environments using state of the art technologies. This course is designed for computer and system infrastructure designers, developers, business managers, entrepreneurs and investors within the cloud computing related industry.


    Introduction, Parallel and Distributed Systems, Cloud Infrastructure, Cloud Types and Services. Applications and Paradigms, Resource Virtualization, Resource Management and Scheduling, Networking Support, Storage System, Cloud Security, Complex Systems and Self Organization, Cloud Application Development. Related case studies.

  5. CS-565 Data Encryption

    CS-565 Data Encryption

    This course basically deals in how data can be kept secure and private. It covers both basic understanding and effective use of tools for information hiding and encryption to protect digital data and communications. Along with the fundamental concepts, Classical cryptography, modern cryptography, and steganography are also covered in this course.


    Basic Concepts, Data Encryption standards, Mono-alphabetic Substitution Ciphers, Stream Ciphers, Transposition Ciphers, Poly-alphabetic Substitution Ciphers Public-Key Cryptography. Data Hiding: Data Hiding in Text and images and other methods. Advanced concept: Convolution, Galois Fields, Hashing, Cyclic Redundancy Codes.

  6. CS-566 Data Mining

    CS-566 Data Mining

    Data Mining deals with the concepts and techniques of discovering useful knowledge from the collected data.

    This course provides in-depth overview of data mining and integration of related concepts and tools. The course also focuses in machine learning concepts as well as practical solutions on applying machine learning tools and techniques in real-world data mining situations.


    Basic concepts, Numeric Attributes, Categorical Attributes, Graph Data, Kernel Methods, Highdimensional Data, Dimensionality Reduction. Mining: Itemset Mining, Sequence Mining, Graph Pattern Mining. Clustering: Pattern and Rule Assessment, Representative based Clustering, Hierarchical Clustering, Density based Clustering, Spectral and Graph Clustering, Clustering Validation. Classifiers: Probabilistic Classification, Classification Assessment, Support Vector Machines, Linear Discriminate Analysis. Related software tools.

  7. CS-567 Data Warehousing

    CS-567 Data Warehousing

    This course covers the concepts and techniques in the design and construction of high-performance data warehouses. The business, software, hardware, and design factors influencing successful implementations of the data warehouse will be emphasized. Both relational and dimensional data modeling for data warehouse implementations will be discussed.

    Distinction between Decision Support System (DSS) and Online Transaction Processing (OLTP) workloads will be made with an emphasis on performance characteristics and functionality required. Furthermore, recent developments in OLAP and ETL algorithms and systems will be highlighted.


    Data Warehousing (DW) Fundamentals; Need for a DW; Operational vs Decision Support Systems; The Building Blocks of DW; Evolution and Trends; Planning and Project Management; Defining the Business Requirements; Architectural Components; Infrastructure as the foundation for DW; Dimensional Modeling; Data Extraction, Transformation and Loading; Data Quality; Physical Design; Data Mart Design; Web Data Warehousing; Relevant Software Tools.

  8. CS-568 Decision Support Systems

    CS-568 Decision Support Systems

    A Decision Support System (DSS) is a computer system that encompasses mathematical models, informational databases and a user interface to help managers make better decisions. The primary focus of this course is developing intellectual capabilities related to design and development of decision support systems. It further aims to give working knowledge of DSS for facilitating the process of semi-structured decision making. This will involve improving hands-on skills using spreadsheet and other tools for building state-of-the-art DSSs, especially Web-Based systems that use advanced computing and networking technologies.


    Introduction to Decision Making and Decision Support Systems; DSS components – Data, Model and User Interface components; Intelligence and Decision Support Systems; Designing, Implementing and Evaluating a Decision Support System; Executive Information and Dashboards; Group Decision Support Systems.

  9. CS-569 E-Business Management

    CS-569 E-Business Management

    This course intends to gain an understanding of the theories and concepts underlying e-business. It will develop familiarity with current challenges and issues in e-business and e-commerce and with the skills needed to work in any e-Business environment and to decide on strategic business decisions related to e-Business. It will develop the realization of the ethics and professional issues in an e-Business Environment.


    Introduction to e-Business and e-Commerce; E-commerce fundamentals; E-business infrastructure; e-environment; e-business strategy; Supply chain management; e-procurement; e-marketing; Customer Relationship Management; e-business implementation; Standards and Relevant case studies addressing critical problems.

  10. CS-570 Enterprise Resource Planning

    CS-570 Enterprise Resource Planning

    Enterprise systems are a category of information systems which have been heavily adopted in practice since the 1990s. They are usually based on packaged software products and drive for cross-functional integration and require organization-wide resources for their implementation. This course is designed to provide a comprehensive insight into theoretical foundations, concepts, tools and current practice of enterprise systems. A mixture of lectures, exercises and case studies will be used to deliver the various topics in this subject.


    Business Functions and Business Processes; The Development of Enterprise Resource Planning (ERP) Systems; Marketing Information Systems and Sales Order Process; Production and Supply Chain Management Information Systems; Accounting in ERP systems; Human Resource Processes with ERP; Process Modeling, Process Improvement and ERP Implementation; Contemporary ERP systems and tools; Relevant case studies addressing critical problems.

  11. CS-571 Information Systems Auditing

    CS-571 Information Systems Auditing

    Dependence on information technology in every aspect of life has elevated the importance of controlling and evaluating information systems. A well-defined and standard process for auditing information systems and the technology is now becoming a necessity for organizations in order to manage the risks associated with technology.

    This course is designed to give a global vision of auditing and control, exposing the major techniques and methods. It will provide guidelines for auditing the crucial areas of IT--databases, security, maintenance, quality, and communications


    Technology and IT Audit Function Knowledge, IT Risk and Fundamental Auditing Concepts, Standards and Guidelines for IT Auditing, Internal Controls Concepts Knowledge, Risk Management of the IT Function, Audit Planning Process, Audit Management, Evidence and reporting Process, Protection of information assets, Logical and applied Security, Support Tools and Frameworks, Foiling the System Hackers, Advanced IT Auditing, Auditing Linux / Windows system, Ethics and Standards for the IS Auditor.

  12. CS-572 Internet Traffic Engineering and Management

    CS-572 Internet Traffic Engineering and Management

    Internet traffic has undergone significant increase with the development of new architectures as well as emergence of new distributed services like social networking and voice/video over IP applications. This course will offer insights into the data profile Internet traffic, its routing fundamentals and accounting/tariffing principles and new challenges. Policies and international standards will also fall under the scope of this course.


    Introduction to governing protocols of Internet, Emerging technologies in Internet, Traditional Traffic engineering, Accounting, tariffing and management issues in Internet traffic, Policies in Internet traffic management (technical and non-technical aspects), Service Level Agreements, Standards and regulations, Convergence of services and management issues, Value added services.

  13. CS-573 Network Security

    CS-573 Network Security

    The dependence of human society on Computer Networks has significantly increased in every aspect, e.g., education, finance and health care. Therefore it is essential to understand and contribute towards the development and security of computer networks. This course will educate students about technical and managerial aspects of network security and will enable them to implement computer networks which are safe from any Cybercrimes and illegal activities.


    Security issues in Internet protocols: TCP, DNS, and routing, Network defense tools: Firewalls, VPNs, Intrusion Detection, and filters, Unwanted traffic: denial of service attacks, Mobile platform security models: Android and iOS, Mobile threats and malware, Web application security, Session management and user authentication, Overview of cryptography, HTTPS: goals and pitfalls, Dealing with legacy code: sandboxing and isolation, Principle of least privilege, access control, and operating systems security.

Non-Credit Courses

  1. CS-411 Computer Systems Fundamentals

    CS-411 Computer Systems Fundamentals

    This non-credit course is aimed to give fundamental knowledge to the students in the core areas of computer systems namely Computer Architecture, Operating Systems and Computer Networking. Sufficient background in these areas is essential for the students to facilitate advanced learning in distributed systems, data engineering and information systems. As there might be many students, enrolled in this program, without having studied such relevant courses at their undergraduate level of studies, it would be mandatory for them to take this course.


    Computer Architecture:

    Instruction Set Architecture – Instruction Formats, Addressing Modes. Computer Arithmetic; Memory System Design: Memory Hierarchy, Cache Memory; Input/Output: Bus Standards, Programmed I/O; Interrupt-Driven I/O. Interrupt Processing, Direct Memory Access (DMA).

    Operating Systems:

    Objectives and Functions; Process Management: States, Description and Control; Process vs Threads; Mutual Exclusion; Memory Management - Virtual Memory; File Management - Organization and Access.

    Computer Networking:

    Network Types and Topologies; Transmission modes; Standardization and OSI reference model; The TCP/IP reference model; IPV4; Subneting.

  2. CS-412 Data Structures and Databases

    CS-412 Data Structures and Databases

    This non-credit course is aimed to give fundamental knowledge to the students in the core software areas of computer systems namely Data Structures and Databases. Sufficient background in these areas is essential for the students to facilitate advanced learning in distributed systems, data engineering and information systems. As there might be many students, enrolled in this program, without having studied such relevant courses at their undergraduate level of studies, it would be mandatory for them to take this course.


    Data Structures

    Introduction and classification of Data Structures; Complexity Analysis of Algorithms; One- and Two-dimensional Arrays: Searching and Sorting Algorithms. Stacks and Queues. Trees – Terminology; Binary Trees: Traversal Algorithms; Graphs – Terminology; Shortest Path Algorithms. Hashing Schemes.


    Basic Definitions; Schema vs Instance; Benefits of Database Approach; Database System Architecture; Entity-Relationship Data Model; Relational Model and Relational Algebra; Functional Dependencies and Normal Forms; Introduction to SQL programming; Indexing in databases; Introduction to Transaction Management.