What do you know about the Hierarchical Data Model?

The hierarchical data model organizes data in a tree structure. There is a hierarchy of parent and child data segments. This structure implies that a record can have repeating information, generally in the child data segments. Data in a series of records, which have a set of field values attached to it.

It collects all the instances of a specific record together as a record type. These record types are the equivalent of tables in the relational model, and with the individual records being the equivalent of rows. To create links between these record types, the hierarchical model uses Parent Child Relationships.

What do you know about the Network Model?

The popularity of the network data model coincided with the popularity of the hierarchical data model. Some data were more naturally modeled with more than one parent per child. So, the network model permitted the modeling of many-to-many relationships in data.

The basic data modeling construct in the network model is the set construct. A set consists of an owner record type, a set name, and a member record type. A member record type can have that role in more than one set, hence the multiparent concept is supported. An owner record type can also be a member or owner in another set.

What do you know about the Relational Model?

(RDBMS – relational database management system) A database based on the relational model developed by E.F. Codd. A relational database allows the definition of data structures, storage and retrieval operations and integrity constraints. In such a database the data and relations between them are organised in tables. A table is a collection of records and each record in a table contains the same fields.

What are the basic properties of Relational Tables?

• Values Are Atomic
• Each Row is Unique
• Column Values Are of the Same Kind
• The Sequence of Columns is Insignificant
• The Sequence of Rows is Insignificant
• Each Column Has a Unique Name

What do you know about the Object Relational Data Model?

• Object/relational database management systems (ORDBMSs) add new object storage capabilities to the relational systems at the core of modern information systems.
• These new facilities integrate management of traditional fielded data, complex objects such as time-series and geospatial data and diverse binary media such as audio, video, images, and applets.
• By encapsulating methods with data structures, an ORDBMS server can execute comple x analytical and data manipulation operations to search and transform multimedia and other complex objects.

What do you know about the Object-Oriented Model?

• Object DBMSs add database functionality to object programming languages. They bring much more than persistent storage of programming language objects.
• Object DBMSs extend the semantics of the C++, Smalltalk and Java object programming languages to provide full-featured database programming capability, while retaining native language compatibility.
• A major benefit of this approach is the unification of the application and database development into a seamless data model and language environment.

Would you please tell us some of the Dr Edgar F. Codd rules of RDBMS?

• Rule 1: Information Rule
• Rule 2: Guaranteed Access Rule
• Rule 3: Systematic Treatment of NULL Values
• Rule 4: Active Online Catalog
• Rule 5: Comprehensive Data Sub-Language Rule
• Rule 6: View Updating Rule
• Rule 7: High-Level Insert, Update, and Delete Rule
• Rule 8: Physical Data Independence
• Rule 9: Logical Data Independence
• Rule 10: Integrity Independence
• Rule 11: Distribution Independence
• Rule 12: Non-Subversion Rule

What do you know about the E-R Diagram and As a Database Developer, have you ever designed E-R Diagram for Database System?

An entity-relationship diagram (ERD) is a data modeling technique that graphically illustrates an information system’s entities and the relationships between those entities. An ERD is a conceptual and representational model of data used to represent the entity framework infrastructure.

The elements of an ERD are:

• Entities
• Relationships
• Attributes

What do you know about the Logical Data Independence and Physical Data Independence?

Logical Data Independence:

Logical data is data about database, that is, it stores information about how data is managed inside. For example, a table (relation) stored in the database and all its constraints, applied on that relation.

Logical data independence is a kind of mechanism, which liberalizes itself from actual data stored on the disk. If we do some changes on table format, it should not change the data residing on the disk.

Physical Data Independence:

All the schemas are logical, and the actual data is stored in bit format on the disk. Physical data independence is the power to change the physical data without impacting the schema or logical data.

For example, in case we want to change or upgrade the storage system itself − suppose we want to replace hard-disks with SSD it should not have any impact on the logical data or schemas.

What is the Logical Processing Order of the SELECT statement?

• FROM
• ON
• JOIN
• WHERE
• GROUP BY
• WITH CUBE or WITH ROLLUP
• HAVING
• SELECT
• DISTINCT
• ORDER BY
• TOP

What is OLTP (Online Transaction Processing)?

In OLTP – online transaction processing systems relational database design use the discipline of data modeling and generally follow the Codd rules of data normalization in order to ensure absolute data integrity. Using these rules complex information is broken down into its most simple structures (a table) where all of the individual atomic level elements relate to each other and satisfy the normalization rules.

What is OLAP (Online Analytical Processing)?

OLAP is an acronym for Online Analytical Processing. OLAP performs multidimensional analysis of business data and provides the capability for complex calculations, trend analysis, and sophisticated data modeling.

What is the main difference between Database Normalization and Database Denormalization?

Database normalization is the process of organizing the fields and tables of a relational database to minimize redundancy. Normalization usually involves dividing large tables into smaller (and less redundant) tables and defining relationships between them. The objective is to isolate data so that additions, deletions, and modifications of a field can be made in just one table and then propagated through the rest of the database using the defined relationships.

Denormalization is the process of attempting to optimize the read performance of a database by adding redundant data or by grouping data.In some cases, denormalization is a means of addressing performance or scalability in relational database software.

How to Remove Trailing Character from Number Column?

SQL Server: Script to Remove Trailing Character from Number Column

Would you please write a script to First Sunday of Next Month using EOMONTH function of SQL Server 2012?

SQL Server 2012: Find First Sunday of Next Month using EOMONTH

In this post, I am sharing a small note about the Key Value Store NoSQL Data Model.

The Redis and Riak are popular key-value store NoSQL Database.

What exactly it is?

In the RDBMS system, we have a table with unique key and values. We are also fetching values basis on a key.

The Key Value Store Data Model is also very similar to RDBMS structure.
In a Key Value Store Data Model, we have a key in left side and value in right side.

The Key Value Store Date model is same as a dictionary or hash model.

It is a schema-less format, and it is just about what you need to store.
A unique key value index the data, and each value can have independent format and stored as BLOB, JSON.

The group of keys and value stores into a Bucket and we can perform different manipulations on each Bucket.
The Bucket may have a different set of fields for every record.
Because of this structure, it is very flexible and scalable up to N level.

You can go with this:

• When we are doing a bulk insertion and write operations
• When we are creating simple and flat data model
• When we are reading the data using only Primary Key

You cannot go with this:

• When we are working with relationship related data
• When we are doing multikey operation like INSERT, UDPATE, DELETE using one KEY at a time
• When we are searching the data using a value

Now time to discuss about the different Data model of NoSQL Databases.

One of the most popular data model is, NoSQL Column Family Store Data Model.

Facebook’s Cassandra, Google’s BigTable Amazon DynamoDB and HBase are the most popular column stored base NoSQL Databases.

What exactly it is?

It allows you to store data with the key and mapped value to it, but these values are stored in Column Family.

A Column Family is a collection of rows, which can contain any number of columns for the each row.
You can create unlimited columns in a row; there are no any limitations.

The row key must be unique within a column family, but the same row key can be reused in another column family.

We can also use different data types for each row key.
e.g. User-1 wants to use a Mobile Number as row key, and User-2 wants to use an Email address as the row key.
This is possible.

Very simple term, we can say that Column Family is a logical division of similar data.
e.g., Column Family-1 for User’s Profile and Column Family-2 for User’s Friends.

A Column family is a very similar to the Table of RDBMS.

How exactly it works?

Keyspace: Name of the application. e.g.Gmail, Facebook.
ColumnFamily: Structure contained unlimited columns.
Column: Tuple with Name, Value, Timestamp.
Key: Name of the record.
SuperColumn: Containter of the more columns.

Each column has three attributes. The column name, column value and Timestamp. Timestamp automatically attached to the each column.

Using the Timestamp, we can also set expiring usage.
e.g. I want to delete a particular column in next 8000 second.
A real-time example is, Running a promo code or special offer for a set of users and running for the particular time. For this kind of application, we can expire a column by defining timestamp.

All the row keys and column stored in the particular order.

We can also create a Super column, which adds another level of nesting to the regular column family structure.

Each Column Family stores in a file and each file separately stores into Disk.
The benefit of storing data in the column is fast searching and accessing of the data.

For example, we have two column family one for User’s Profile and second for User’s Friends.
Now, I want to fetch User’s Profile data; then It accesses only a User’s Profile file which returns good performance.

Another good example is,
Cricketer’s award information. All cricketers have different award information like International, National and State level matches.
We can store an N number of different award information for each cricketer and stores vertically into Column Family.