IT Enablement Approaches

• Large Business may have hundreds of processes to be enabled by IT.

• Several Types of Application may be deployed– Departmental IT Applications (Payroll)– OLTP application (Net Banking, Reservation)– Business Model application (OLX , Snapdeal)– Decision Support– MIS– ERP

IT enablement approaches– Inhouse Development (Bespoke Application)– Design and Implementation Inhouse &

development outsource– Procure Global licensed software– Totally outsource all processes

• Hardware• Software• Tools• Maintenance

– Hybrid

IT infrastructure

• Enterprise Maintains different IT infrastructure (3 or More)– Development– Testing – Production systems & Data centres (Private

Cloud)• Protection and Security is an important

issue

Important Points• All IT applications required to run an enterprise

will never be created at same time. • There will be several generations of applications

developed or purchased over several years– Legacy– Modern Net based

• All IT applications need maintenance as business rules and business environment changes rapiidly

• Enterprise may have different H/w , S/w, OS, RDBMS for different applications. Data format may also be different.

• Enterprise may different approaches for application development

• Some applications may be loosely connected through portal but may have limitations in terms of data exchange

• Enterprise may have vast amount of past data. (Warehouse)

• Some data may in proprietary form

Information Users

• Data is asset• Right Information to right user• More and More net based access.• Many User groups

Information Users

• Employees, Partners, suppliers, customers, investors, analysis, prospective employees.

• Office goers, mobile users, home office users.

• Business leaders, decision makers, operation managers, project managers, executives

Users contd..

• Role based users• Secured Users (VPN)• Admin users• Analytical users• Multidevice access users

Expectations and Requirement

• Smooth authentication • Authorized access• 24*7 , 365 days availability• High Speed of delivery• Secure delivery• Secured commit or rollback• Accurate and consistent Information• Any time, Anywhere and device specific info

Types of Digital Data

• Data is most valuable asset.• Three forms of data

– Unstructured– Semi structured– Structured

Unstructured Data

• This data does not conform to any data model or its not in a form which can be used easily by a computer program.

• It cannot be stored in rows and columns• Memos, Chat rooms, PowerPoint

presentations, Images, Videos, Letters, White papers, email content,blogs etc.

Semi Structured

• This data also does not conform to any data model but it can be used easily by a computer program for example, email Headers, XML, HTML.

• Metadata is available but not sufficient.

Structured Data

• This data is in some organized form and conforms to a data model.

• Stored in a standard format (Tables Etc)• Relationship exists

Characteristics of Structured Data

• Conforms to a data model• Similar entities are grouped• Attributes in a group are same• Definition format and meaning of data is

same• Data is stored in the form of rows and

columns • Data resides in fixed fields

Sources of Structured Data

• DBMS• Spreadsheets• OLTP Systems

Benefits of Structured Data• Storage is easy and systematic• Scalability is easy with the increase in data• Ensuring Security is easy• Manipulation is easy• Easy Retrieval

– Query Based retrieval is easy– Indexing and Searching– Mining is easy– BI operations are easy to implement ( Data

Warehousing)

Characteristics of Unstructured Data

• Difficult to manage• Difficult to determine to meaning• Does not follow any rules or semantics• No standard data types• No Specific Structure• Does not conform to any data model• No particular format or sequence• Cannot be easily used by a programme

Sources of Unstructured Data• Web Pages• Memos• Videos• Images• Body of email• Word Files• PPT• Chat• Reports• White papers• Surveys• BLogs

Managing Unstructured Data

• Indexing– Not as easy as DBMS, Based on name , date

only• Tags / Meta data (Word File properties,

MP3 Songs Properties , Winamp alt 3) – But difficult to manage

• Classification is difficult

Drawbacks/Challenges of Unstructured Data

• Difficulty in storage because no specific structure ( Eg Store Photo in DB or Outside Application V V Imp)

• Scalability : difficulty to control • Retrieval is not easy• Less secured• Manipulation is difficult• Difficult to Index• Different File Formats

Solution to storage of Unstructured Data

• Changing Format ( IBM Video to Text)• Developing and Using new hardware• Storing in DBMS (LOB and BLOB)• Storing in XML format• Content Addressable Storage ( See eg)

– It organized files based on their metadata and assign unique name to every object stored in it.

Semistructured Data

• Does not conforms to any data model• Cannot be stored in rows and columns• Difficult to determine the meaning• They have some metadata but still not

sufficient for management and automation of data.

• The Entities are grouped but the properties within a group may not be same.

Sources of Semistructured Data

• Email Headers ( From , To , Subject , CC)• XML• Network Packets• Binary Files• Zipped Files etc.• XML is self describing because data can

exist without schema

Issues of Semistructured Data

• Storage Cost• Irregular and partial structure• Evolving schemes• One important difference between Semi

and Structured is that semi structured requires looking at the data itself to determine structure as opposed to structured data that requires looking at the structure only.

Extracting Information

• Indexing• OEM• XML• Mining Tools

OEM Example

• example may be written as { book: { author: "Coetzee", title: "Disgrace", year:

1999 } }