Unexplained Thoughts!

She didn't knew that someone was waiting for her.
She didn't knew that she meant the whole world to someone.
She didn't knew that someone was making continuous efforts for her.
She didn't knew that someone was silently praying for her.
She didn't knew that someone had so many dreams with her.
In fact she didn't knew that someone was planning to spend his whole life with her.
She didn't knew that someone was there for her every time.
She didn't knew that someone died to have her glimpse.
She didn't knew that someone remembered her in every moment of his life.
She didn't knew that she was the first to be remembered after waking up and last to be remembered after falling asleep.
She didn't knew that she was every thing to him.
Indeed he could never explain!

My Value!

I calculate my value by the no of faces I make smile.
I calculate my value by the goods I do to the people.
I calculate my value by the efforts I make to keeps things going.
I calculate my value by the togetherness I create.
I calculate my value by the sacrifices I make for others.
I calculate my value by the pain I take for others.
I calculate my value by the compromises I do.
I calculate my value by the time others wish to spend with me.
I calculate my value by the times I was there when people needed me.
I calculate my value by the no of times I complemented them in their bad times.
I calculate my value by the no of times people acknowledge me.
I calculate my value by the rigorous efforts I make to make it memorable.

Questions from a Lover

I don't know how long it will take to bring you next to me.
I even don't know you will ever come next to me.
I don't know why I am doing this.
I don't know why do I see you everywhere.
I don't know why I fought with my parents to meet you.
I don't know I was so eager to have your glimpse.
I don't know what attracted me towards you.
I don't know why do I remember all the moments that we had spent together.
I don't know why do I remember everything about you.
I don't know the price I will be paying for your love.
I don't know the sacrifices I will be making for your love.
But I know one thing and that is I Love You!

Hello folks!

This time I am back with a poem. I am happy to say that I have started writing poems and this is my debut poem. I hope you like it.

Things have started to look very far fetched now.
Not sure of what is right but I am sure of one thing and that is to fight till the last.
I don't know how long it is going to take, but I am sure of one thing and that is to fight till the last.
Many things will come in between, but I will make sure one thing and that is to fight till the last.
It is very easy to begin something new but to hold on is very difficult and again I will make sure that I fight till the last.
Definitely there will be someone pulling my leg but I will make sure that I fight till the last.
I am also having critics but I will make sure that I fight till the last.
At a stage I felt to give up but again I made sure that I fight till the last.
Again and again I will make sure that I fight till the last!

Enterprise Resource Planning 

What is ERP?

Enterprise resource planning is basically a Information technology business system which integrates all the basic structures of business planning and management. It is basically a planning of how the resources are move from one place to another. ERP can also be refereed as an integrated view of resource planning. ERP is a multibillion Dollar industry. It also allowed error free transactions. There are two key components in ERP. The first key component is common database. This is a very helpful component. Common database reduces so many problems. Common database provides the access to everyone attached to that particular database. With the help this common database the feeding of the data is to be done once which could bring transparency and lead to standardisation. We can also retrieve information at real-time. 

The second key component which ERP includes is modular software design. This directly implies that this will allow the selection of modules which are required. They also mix and match the modules and lead to the required module. This will lead to improvement in business performance. ERP system can also be considered as a software package. The introduction of the term ERP replaces two or more independent applications. And this could eliminate the requirement of external interfaces. ERP also allowed to have a proper maintenance of the production which is a very key component in resource planning.

As ERP is basically a software. Advantages of using software are as follows:-

(1)    Avoids human errors:- The biggest advantage of using ERP is that it avoids human errors. With the help of this we can avoid very big and costly errors. This can also be a double checker software which would enable us to keep an eye on the human errors.

(2)    Avoid unnecessary overstocking:- With the help of this we are able to manage and analyse our stock. And due to this we can avoid overstocking.

(3)    Reduce paperwork:- This is the need of 21^st century. By using this software we can reduce the paperwork.

Origin

The Gratner group had used this term Enterprise Resource Planning. This term was used in the early 1990’s. Terms such as  material requirement planning (MRP), manufacturing resource requirement planning (MRP II) and computer integrated manufacturing are the extended are those which extend the capabilities of Enterprise resource planning. Without replacing these terms Enterprise Resource Planning came in to effect to represent the resource planning model which ultimately reflects the evolution of application integration beyond manufacturing.

Later another Enterprise resource planning(ERP II) came into action known as ERP(II). It was launched in the 2000’s. This ERP(II) was  more flexible than the ERP(I).  ERP(II) led to many key things such as Globalisation, transparency, standardisation. With the help of globalisation this enabled organisations to share data with the other organisations also. By increasing the transparency it allowed to remove the confusions and saved a lot of time.  ERP(II) is the extended version of ERP(I). It also led to the optimization of resource planning. Earlier the ERP(I) was only used in back office work but ERP(II) was modified such that it was used in both back office as well as front office. Later even the Government and the Non Profit Organisations(NPO’s) started to use this ERP model

ERP has five main components which are as follows:-

(1)    Supply Chain Management

(2)    Financial management System

(3)    Manufacturing Resource Planning

(4)    Human Resource Management

(5)    Customer Relationship Management

1)    Supply Chain Management

In Supply chain management there are five key components which make a chain:

(1)    Raw materials

(2)    Work-in progress

(3)    Inventory or stock

(4)    Finished goods

(5)    Consumption by customer

The first key component is raw material. In resource planning it is very crucial to manage the raw materials. Proper management could to very effective results. The next component is Work-in progress. With the help of this component the ERP can be more stabilised. Proper management of the next component which is inventory or stock is very vital. Inventory could lead to proper management of the resources. Now the finished goods are another component which is to be designed as per the consumer. The final component is the consumption by customer. This is the last step in the supply chain management.

Hence, Supply chain management is basically the flow of goods.

(2)    Financial Management System

Financial management system is a method by which companies or organisations monitor there:-

(1)    Income

(2)    Expense

(3)    Assets

The main objective of this system is to maximise the profit. It also tries to ensure sustainability. There are certain ways in which financial system can be effective. And those are as follows:-

(1)    Streamlining Invoicing

(2)    Bill Collection

(3)    Eliminating accounting errors

(4)    Minimizing record keeping redundancy

(5)    Ensuring compliance with tax

(6)    Offering flexibility

This can be done by keeping all payments and receivables transparent. This is the most crucial step in financial management system. The next we need to follow is keeping track of all the liabilities we have.  Here we also need to balance multiple bank accounts. With the help of this the accounting section could also be managed and could lead to accuracy. The best step would be to minimize the paper work. By minimizing paperwork it could lead to a lot of profit.  While managing our finance system we need to keep a very important aspect in our mind which is the security.  Ensuring the security is very important. At last we just need to coordinate our balance sheets, income statements, and expense statements.

(3)Manufacturing Resource Planning

Manufacturing Resource Planning is evolved from Material Requirement Planning. The main objective of this is to ensure that enough products are available as per the requirement of the customer. Management of material is very important in this. As per the customer needs proper updates are very important to make sure proper resource planning takes place. For small scale businesses manufacturing resource planning is very costly.  Also this process could consume a lot of time which may lead to wrong calculations of the market.

(4)    Human Resource Management

The first thing we need to focus here is training. In Human Resource training is very important. This could lead to proper development of resources. Also proper recruitment is very crucial in this process.  Skills are the most important in this which are needed to pay more emphasis. Communication is the first priority while observing the skills. Attendance is another thing which helps a lot in developing and managing the Human Resource development. Payroll classifies the above all. The higher payroll leads to more advancement of these skills.

It comprises of five management strategies.

(1)    Personnel Management

(2)    Organizational Management

(3)    Payroll System

(4)    Time Management

(5)    Personal Development

(5) Customer Relationship Management

The main objective of this model is to make sure that the customer is satisfied with the goods and services provided. It is very important to provide timely services to the customer. Managing customer services is very crucial. Keeping in mind the various needs of the customer we need to plan. The best way to deal customers would be to make the customers feel important. This strategy could lead to enormous amount of response from the customer. With this the other strategy that is customer satisfaction could also be achieved.

Role of ERP in Supply Chain

Integration of supply chain and ERP makes the distribution and business possible. ERP plays a very vital role in supply chain management. Here are various roles which ERP plays in supply chain.

(1)    Supply Chain Planning:-  Firstly it includes the determination of the stock and inventory system.  It also allows to decide the various promotional strategies.

(2)    Purchasing Procurement and Execution:- ERP provides a efficient way to handle the goods i.e the stock with the help of this we can handle the stock also.

(3)    Monitoring and Maintenance:- We can monitor the supply chain process with the help of ERP. Further the maintenance could also be done with the help of this.

A successful organization must be able to manage the supply chain by effectively using the ERP.  The difference in ERP and Supply chain is that the focus in supply chain is optimization over the entire chain whereas in ERP the focus is on optimization within a single organization.  The same is the case with the scope of these two. In Supply chain the scope is integrating all inter - organizational activities whereas the scope of ERP is integrating all activities within a single organization.

Big Data In a Nutshell

 Introduction 
 

Presently the importance of big data is being realised very slowly. Big data is complex data for which advanced methods are required to get a certain value.  Here the size of data is such that it goes beyond the ability of the software tools to capture, process and calculate the data.

 As it is fluctuates every moment   accuracy plays a very important role. Better accuracy can lead to good decisions. As a result of which growth will take place. I have summarised the definition of big data as per various research papers.

        

In 2010, Apache Hadoop defined big data as “data sets which could not be captured , managed and processed by ganaral computred within ageneral computer with acceptable scope”. Here Apache tries to tell that the complex data which cannot be maintained with the help of other softwares .

 This requires a high level technique and technology. The Gartner group defines big data as three dimensional data growth challenges and opportunities as the 3v’s.

(1)   Increasing volume – This directly says to increase the volume of the data. This data does not sample. It directly grows and observers the track and what happens to this data.

(2)   Variety – Variety refers to the range of the big data. It is very important to understand the variety of big data. It tells us that from where the big data will be drawn.

  Nowadays the data is growing very rapidly. Currently the World’s per capita capacity to store data is being doubled every 40 months. This implies that every 40^th month we require a new technology.  2.5 exa bytes  of data is being created every day. This data is gathered from various  software logs, cameras, microphones, radio frequency identification devices(RFID), mobile devices.

With big data many important things of the field of technology are related. Things such as cloud computing and big data play a very vital role for the advancement of technology. Big data also has certain challenges which are needed to overcome.

Big data is one field which directly relates to decision making. Simply with the help of charts, graphs we could lead to some excellent decisions.

 

 History 

 

This started seven decade ago. Earlier this was refereed as “information explosion”. This was the term firstly used in the oxford dictionary. Our increasing ability to store and analyze data has been a gradual evolution. The main evolution of big data started at the end of the last century and this took place because of the invention of digital storage and internet.

 As the usage of the term big data has increased now it all began with the literature. Various novels, articles were written for the better understanding of this term. In 2008, it was estimated that 14.7 exabytes of information was produced. According to the reports the data was going on increasing.

 In 2014, the rise of mobile machines took place. The people started to use mobile devices to access digital data. Now big data analytics is becoming a top priority for the business. Currently big data is not a new phenomenon but one that had a long evolution of capturing and using data. Big data is also laying the foundations on which many evolutions will be built.

Four Layers 

There are four layers in Big data. Those are as follows:-

(1)   Data source layer:-

This is the first layer of the Big data. In this layer the arrival of data takes place. For this we first need to analyse whatever we have. Then the next step is to find out what do we need to answer. For this analysis of question is very important.  This helps to establish new sources for data.

(2)   Data storage layer:-

After collecting data from the first layer. The next step begins. In this step volume of data enterprises begins to generate and the storage starts to explode. For smaller data sets all that is required is a bigger hard disk.

 Now when you move on to huge data the requirement of file system comes. You must have a system that understands the file system and that can handle the database that is being generated.

Depending on the amount of data you are storing you need to make a decision of what are your security and privacy requirements

(3)   Data processing layer:-

As the name suggests the analysis of data takes place in this layer. This is the most crucial layer of the big data. This layer enables to reach out to a particular solution.

could be done by preparing charts, graphs from the analysed data. Presenting the data as simple as it could be is the key feature which allows to take quick and right decisions.

Technology

Aim:-  Real or Real time delivery of information.

 For handling data various technologies were used such as Relational Database Management system (RDBMS), Dekstop statistics and visualization packages . But these fail when big data comes in to act. Users of big data prefer direct attached storage (DAS). This also has many forms like Solid State Drive (SSD). 

With the help of this the capacity of the SATA disk increases which is buried inside parallel processing nodes.  While using technology it must be assured that latency is kept in mind.  Wherever possible it is tried that latency could be avoided.  Advancement of technology in big data is very crucial. Proper advancement in this could lead to exact conclusions. By producing exact conclusions one could easily predict the trends which the market is following and could be very helpful in predicting the market.

Various technologies such as these are used in handling various big data :-

(1)   A/B Testing

(2)   Machine learning

(3)   Natural Language Processing(NLP)

(4)   Cloud Computing

(5)   Business Intelligence

(6)   Charts

(7)   Graphs

Applications

Cloud Computing :-

Cloud Computing is the delivery of computing services over the internet. Cloud Computing allows the users to access software and hardware that are accessed by third parties at remote location.

 It is a model for enabling convenient, on demand network access to shared pool of configurable  computing resources that can be rapidly provisioned and released with minimal management efforts on service provider interaction.

Cloud model consists of five characteristics:-

(1)   On demand self service:-

A customer can unilaterally provision computing capabilities such as server time and new storage, add needed automatically without automatically without requiring human access with each service provider.

(2)   Broad new access:-

The capabilities are available over the network and accessed through standard mechanism that promotes use by heterogeneous thin ir thick client platform such as mobile phone, tablets, laptop etc)

(3)   Resource pooling:-

 The provider computing services are pooled to drive multiple consumer using a multi-tenant model with different physical and virtually resources which are dynamically assigned and redesigned according to the consumer demand.

(4)   Rapid Elasticity:-

 Here this can be easily provisioned and released. In some cases it can take place automatically also. This is done to move up the inward and outward commensurate with demand.

(5)   Measured services:-

This system automatically controls and optimizes resource. This is done by leveraging a metering capability at the same level of abstraction , It is appropriate to the types of services.

 

Relationship between cloud computing and Big data

The development of cloud computing can directly lead to the solutions of the challenges Big data is facing. It very crucial to enhance the development of cloud computing. With the help of cloud computing the storage issue can be solved. This is one of the biggest issue which big data is facing. Another key thing which affects the big data is distributed storage. This can effectively manage big data.

 Cloud computing mainly relates to affect the architecture of the IT industry whereas big data plays a vital role in decision making.  They both are indirectly connected. Therefore, the development of both the things could lead in further advancement and enhancement in the field of technology.

Relationship between Iot and Big Data

In Iot huge amount of sensors are fixed into various devices and machines in the real world. The sensors which are fixed in this devices and machines produce a huge amount of data. This data is being produced from many fields. This could be environmental data, transport data and many others.

Now this huge amount of data generated could be referred to as Big Data. This has its own characterstics. This data could be structured, unstructured or other. It needs to be analysed. For analysis certain graphs, charts are prepared to reach to a certain solution or a conclusion. This conclusion could be helpful in bringing a solution to a problem.

Currently the data processing capacity of IoT has gone down. It is very important to introduce new technology in this field which could lead to the development and hence produce good conclusions which would ultimately give a good solution to a certain problem.