Cloud Computing

(Computing Power delivered to Businesses you only pay for what you Use!)

Contents

1.       What if there is no Cloud Computing
2.       What do we need to Install / Run a Server-Side Application
3.       Why Data Center
4.       Where can we have the Data Center
5.       What is Cloud Computing
6.       How does Cloud Computing work
7.       Categories of Cloud Computing Services/Models
8.       Popular Cloud Service Providers
9.       Important Characteristics of a Cloud
10.       Six Advantages of Cloud Computing
11.       Types of Clouds (in Cloud Computing)
12.       Cloud Service Providers Market Share

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What if there is no Cloud Computing

Around 11 years back (before March 2006), mid-size to large non-IT companies were storing everything in-house i.e., on their own servers.

Ex.s: Banks like SBI, ICICI, AXIS, Citigroup, Bank of America (1000s of Banks worldwide), Telecoms like Airtel, BSNL, AT &T, Verizon, T-Mobile (100s of Telecoms world, Retailers like BigBazaar(Future Group), Landmark(Tata Group), Walmart, Manufacturers like TataMotors, TV Media like NDTV – all of them acquire huge amount of data on a daily basis, Cab services like Ola Cabs.

AWS is used by about 8,000 companies in India to reduce its internal IT staff and cut IT costs by over 80 percent.

But over the years with internet speed becoming better, people discovered a new way to store everything, the “Cloud” way! What is a Cloud? To understand what is Cloud, let’s first understand why it came into the picture!

Before “Cloud”, companies were storing everything offline i.e hosting websites on their on-premise servers, and adding more servers whenever required. But, there were some problems with this kind of setup. What were these problems?

•     You own a company/institution which runs a very successful website and let’s imagine the “cloud concept” was not introduced at this time. Therefore your website was hosted on the on-premise servers. Seems normal, right?
•     One fine day, you added a new feature to your website which became a hit overnight. Now, your traffic increased multi-folds and the inevitable happened, your website crashed!
•     Woah! That hurts, isn’t it? Well, you obviously couldn’t have foreseen this, and even if you did, there was no way you could have spent and bought the required servers, in such a short time. Why? Well, servers are not cheap guys, they are very VERY expensive.

Let’s say you can afford these many servers, but are you sure about experiencing this much traffic every day? After you bought the servers and the next day your traffic dropped, what will you do with these servers now? They will be idle most of the time, and hence they become a bad investment on your part.


Now with this example, let’s summarize the problems with the private model in this Azure Tutorial:

•     This setup is expensive.
•     Your servers will be idle most of the time.
•     Every machine is bound to fail one day, maintaining these many servers becomes a tedious task.

To handle these problems we had to come up with a new model of infrastructure. Hence, we came up with Cloud. With cloud computing, all these problems were solved! How?

•     Put your data on Cloud Servers and you are set! No more buying expensive servers.
•     Scalability! Your server capacity will scale up or scale down according to the traffic, that too automatically.
•     Your cloud provider will manage your servers, hence no worries about the underlying infrastructure.

What do we need to Install / Run a Server-Side Application

Ans: Infrastructure

• Server Hardware – CPU, RAM
• Network Connectivity Equipment – Hubs, Switches, Routers, Cables
• Storage - HDD
• Operating System (Windows or Linux)
• Licenses for Software
• Virtualization to get the benefits of Administration, Backup and Recovery, Fault Tolerance etc
• Big Data Hadoop Clusters – cost a lot for setting up Apache Hadoop Clusters
• Power
• Cooling
• Network Admins
• System Admins
• Database Admin

Note: All Infrastructure components are placed in a Data Center instead of in an office cabin of System Administrator.

Why Data Center

•     Cooling
•     Security
•     System Administration
•     Network Administration
•     Physical Space

Where can we have the Data Center

•      Traditionally “On-Premises” on a dedicator floor like TCS, Infosys, IBM, HP etc – a lot of Investment is required
•     “On-Premises Managed Data Centers” whose core business is not IT – Ex.s: Hotels, Banks, Stock Exchanges who are in need of IT. They go for bidding for the project – 5 or 10 years contract with one of the Services companies like TCS. – Still a costly affair
•      In the Cloud – They set up the Data Centers and we the customers (owners of small and big companies) just connect through public internet and use their services.

Note: Due to the boom in Cloud we have boomed in Startups – because they just need to pay for usage like just paying the rent on monthly basis and forget about the rest – like security, furniture, projectors, counselors etc. They are very important because what if you fail in your business, what will happen to the infrastructure you have set up. You have to sell them for a huge loss.

What is Cloud Computing

During the 1890s, each Factory used to generate its own electricity (In-House power generation), later came power Distribution Companies like APEPDCL. Cloud Computing is a similar revolution in IT

Cloud computing is the on-demand delivery of computing power, database storage, applications, and other IT resources through a cloud services platform via the internet with pay-as-you-go pricing.

How does Cloud Computing work

Cloud computing provides a simple way to access servers, storage, databases and a broad set of application services over the Internet. A Cloud services platform such as Amazon Web Services owns and maintains the network-connected hardware required for these application services, while you provision and use what you need via a web application.

Categories of Cloud Computing Services/Models

IAAS (Infrastructure As A Service): The basic layer of Computing (All the Hardware)

A vendor provides clients pay-as-you-go access to storage, networking, servers and other computing resources in the cloud.

End Users: Admins of Small and Mid-Scale and non-IT Businesses

PAAS (Platform As A Service): Runs on top of PAAS

A service provider offers access to a cloud-based environment in which software developers can build, deploy and deliver applications. The provider supplies underlying infrastructure.

End Users: Software/Application Developers who builds software on their own machines but wants to test/run them by deploying on a Server or a Cluster.

Exs: Operating Systems, Web Servers like Apache Web Server, Tomcat, .Net Framework, Node.js etc, Databases like Oracle, MySQL etc, Big Data Hadoop Framework installation and its configuration, Hive installation and its configuration etc

SAAS (Software As A Service): Runs on top of SAAS – Just a Web Browser is sufficient for the Client

A service provider delivers software and applications through the internet. Users subscribe to the software and access it via the web or vendor APIs.

Note: Here users do not have to manage, install or upgrade software; SaaS providers manage this.

In this case usually web browsers, provide the point of access to software running on servers.

Exs: Non-Technical End Users, just subscribe to a Service/Application and use them, ,like: Salesforce, Ms Office 365, Google Apps like Google Drive, Gmail, Google Docs, DropBox, Mediafire, flipkart.com

Note: In the 1^st one, we are not using any Cloud Service, everything is available on the Premises and fully managed by us.

Popular Cloud Service Providers

Infrastructure As A Service (IAAS) - Cloud Service Providers:

Platform As A Service(PAAS) - Cloud Service Providers:

Software As A Service(SAAS) - Cloud Service Providers:

Important Characteristics of a Cloud

•     On-Demand (any time - Mid Night, Early in the morning, Sunday, Holiday)
•     Self-Service (can do anything on your own no need to wait for anybody from the Service Provider)
•     Pay-as-you-go (hourly, daily, monthly etc)
•     Rapid Elasticity (highly scalable)
•     Measured Services (CPU, Storage, Network etc)

Six Advantages of Cloud Computing

•     Trade capital expense for the variable expense (Cost Efficient): Instead of having to invest heavily in data centers and servers before you know how you’re going to use them, you can only pay when you consume computing resources, and only pay for how much you consume.
•     Benefit from massive economies of scale: By using cloud computing, you can achieve a lower variable cost than you can get on your own. Because usage from hundreds of thousands of customers is aggregated in the cloud, providers such as Amazon Web Services can achieve higher economies of scale which translates into lower pay as you go prices.
•     Stop guessing capacity:
  Eliminate guessing on your infrastructure capacity needs. When you make a capacity decision prior to deploying an application, you often either end up sitting on expensive idle resources or dealing with limited capacity. With cloud computing, these problems go away. You can access as much or as little as you need, and scale up and down as required with only a few minutes’ notices.
•     Increase speed and agility:
  In a cloud computing environment, new IT resources are only ever a click away, which means you reduce the time it takes to make those resources available to your developers from weeks to just minutes. This result in a dramatic increase in agility for the organization, since the cost and time it takes to experiment and develop, is significantly lower.
•     Stop spending money on running and maintaining data centers:
  Focus on projects that differentiate your business, not the infrastructure. Cloud computing lets you focus on your own customers, rather than on the heavy lifting of racking, stacking and powering servers.
•     Go global in minutes:
  Easily deploy your application in multiple regions around the world with just a few clicks. This means you can provide a lower latency and better experience for your customers simply and at minimal cost.

Types of Clouds (in Cloud Computing)

These are of three types: Public Cloud, Private Cloud, and Hybrid Cloud

Difference	Private	Public	Hybrid (Combination of Public & Private)
Tenancy	Single tenancy: there’s only the data of a single organization stored in the cloud.	Multi-tenancy: the data of multiple organizations in stored in a shared environment.	The data stored in the public cloud is usually multi-tenant, which means the data from multiple organizations is stored in a shared environment. The data stored in private cloud is kept private by the organization.
Exposed to the Public	No: only the organization itself can use the private cloud services.	Yes: anyone can use the public cloud services.	The services running on a private cloud can be accessed only by the organization’s users, while the services running on public cloud can be accessed by anyone.
Data Center Location	Inside the organization’s network.	Anywhere on the Internet where the cloud service provider’s services are located.	Inside the organization’s network for private cloud services as well as anywhere on the Internet for public cloud services.
Cloud Service Management	The organization must have their own administrators managing their private cloud services.	The cloud service provider manages the services, where the organization merely uses them.	The organization itself must manage the private cloud, while the public cloud is managed by the CSP(Cloud Service Provider).
Hardware Components	Must be provided by the organization itself, which has to buy physical servers to build the private cloud on.	The CSP provides all the hardware and ensures it’s working at all times.	The organization must provide hardware for the private cloud, while the hardware of CSP is used for public cloud services.
Expenses	Can be quite expensive, since the hardware, applications and network have to be provided and managed by the organization itself.	The CSP has to provide the hardware, set-up the application and provide the network accessibility according to the SLA (Service Level Agreement) with the user.	The private cloud services must be provided by the organization, including the hardware, applications and network, while the CSP manages the public cloud services.

So, in Short:

ie., If more control and security is required to go for private. If more scalability is required go for the public. If Applications are deployed on your private cloud but can burst into the public cloud during demand spikes then go for Hybrid.

Cloud Service Providers Market Share

---Knowledge acquired from various resources online and our take on this subject

Blockchain Technology

                              

Contents

1. What is Blockchain technology
2. Popular Blockchain based projects
3. Blockchain Architecture/How Blockchain transaction works
4. Block structure
5. Block hash
6. Block Security
7. Proof of Work
8. Distributed P2P Network
9. Communicating with other nodes
10. Client-Server Network Vs Peer-to-Peer Network
11. Why do we need BlockChain
12. BlockChain Versions
13. Real-Life use case of Blockchain
14. BlockChain Variants
15. What is Mining in BlockChain

What is Blockchain technology

Blockchain can be defined as a chain of the block that contains some information. This technique is intended to timestamp digital documents (Ex.s: land records, stock market shareholding, car resale etc. ) so that it’s not possible to backdate them or temper them.

It is nothing but a distributed database that maintains a continuously growing list of ordered records.

The term “blockchain” is usually strongly tied to concepts like transactions, smart contracts or ryptocurrencies.

The blockchain is used for the secure transfer of items like money, property, contracts, etc. without requiring a third-party intermediary like bank or government. Once a data is recorded inside a blockchain, it is very difficult to change it.

The blockchain is a software protocol (like SMTP is for email). Blockchains could not be run without the Internet. It is also called meta-technology as it affects other technologies. It is comprised of several pieces: a database, software application, some connected computers, etc.

What Blockchain is not

Blockchain is not Bitcoin, but it is the technology behind Bitcoin
Bitcoin is the digital token and blockchain is the ledger to keep track of who owns the digital tokens
You can’t have Bitcoin without blockchain, but you can have blockchain without Bitcoin.

Popular Blockchain based projects

• Bitcoin
• Ethereum

Blockchain Architecture/How Blockchain transaction works

Block structure

The first logical step is to decide the block structure. To keep things as simple as possible we include only the most necessary:

• index
• timestamp
• data
• hash and
• previous hash

Note: The hash of the previous block must be found in the block to preserve the chain integrity

Eg: A Bitcoin Block contains information about the Sender, Receiver, Number of Bitcoins to be transferred.

Block hash

The block needs to be hashed to keep the integrity of the data. A SHA-256 is taken over the content of the block.

Understanding SHA256 – Hash

A block also has a hash. It can be understood as a fingerprint which is unique to each block. It identifies a block and all of its contents, and it’s always unique, just like a person’s fingerprint. So once a block is created, any change inside the block will cause the hash to change.

Block Security

Let’s consider a chain of 3 blocks. The 1^st block has no predecessor. Hence, it does not contain the previous block. Block 2 contains a hash of block 1, while block 3 contains the Hash of block 2.

Hence, all blocks are containing hashes of previous blocks. This is the technique that makes a blockchain so secure. Let’s see how it works:

Assume an attacker is able to change the data present in the Block 2. Correspondingly, the Hash of the Block also changes. But, Block 3 still contains the old Hash of the Block 2. This makes Block 3, and all succeeding blocks invalid as they do not have correct hash the previous block.

Proof of Work

Hashes are an excellent mechanism to prevent tempering but computers these days are high-speed and can calculate hundreds of thousands of hashes per second. In a matter of few minutes, an attacker can tamper with a block, and then recalculate all the hashes of other blocks to make the blockchain valid again.

To avoid the issue, blockchains use the concept of Proof-of-Work. It is a mechanism which slows down the creation of the new blocks.

A proof-of-work is a computational problem that takes certain to effort to solve. But the time required to verify the results of the computational problem is very less compared to the effort it takes to solve the computational problem itself.

In case of Bitcoin, it takes almost 10 minutes to calculate the required proof-of-work to add a new block to the chain. Considering our example, if a hacker would to change data in Block 2, he would need to perform proof of work (which would take 10 minutes) and only then make changes in Block 3 and all the succeeding blocks.


This kind of mechanism makes it quite tough to tamper with the blocks so even if you tamper with even a single block, you will need to recalculate the proof-of-work for all the following blocks. Thus, hashing and proof-of-work mechanism make a blockchain secure.

Distributed P2P Network

However, there is one more method which is used by Blockchains to secure themselves, and that’s by being distributed. Instead of using a central entity to manage the chain, Blockchains use a distributed peer-peer network, and everyone is allowed to join. When someone enters this network, he will get the full copy of the blockchain. Each computer is called a node:

Let’s see what happens when any user creates a new block. This new block is sent to all the users on the network. Each node needs to verify the block to make sure that it hasn’t been altered. After complete checking, each node adds this block to their blockchain.

All these nodes in this network create a consensus. They agree about what blocks are valid and which are not. Nodes in the network will reject blocks that are tampered with.

Communicating with other nodes

An essential part of a node is to share and sync the blockchain with other nodes. The following rules are used to keep the network in sync:

When a node generates a new block, it broadcasts it to the network
When a node connects to a new peer it querys for the latest block
When a node encounters a block that has an index larger than the current known block, it either adds the block the its current chain or querys for the full blockchain.

Client-Server Network Vs Peer-to-Peer Network

Client-Server Network

Centralized Network

Note: Let’s assume the server as a Bank’s Application / Database Server and the clients as ATM Machines, Bank branches, and client’s Web Browsers

Note: Remembers that Server sends the response data to the client only when a client sends a request.

Peer-to-Peer Network

Fig1                                                    Fig2
Decentralized Network

Note: Here each machine is called as a Node/Peer. Each node has equal priority. Any node can be connected to any other node in the network (but not necessarily to all the other nodes).

Why do we need BlockChain

The following are the important reasons why BlockChain technology has become so popular

• Resilience: Blockchains is often replicated architecture. The chain is still operated by most nodes in the event of a massive attack against the system.
• Time reduction: In the financial industry, blockchain can play a vital role by allowing the quicker settlement of trades as it does not need a lengthy process of verification, settlement, and clearance because a single version of agreed-upon data of the share ledger is available between all stake holders.
• Reliability: Blockchain certifies and verifies the identities of the interested parties. This removes double records, reducing rates and accelerates transactions.
• Unchangeable transactions: By registering transactions in chronological order, Blockchain certifies the unalterability, of all operations which means when any new block has been added to the chain of ledgers, it cannot be removed or modified.
• Fraud prevention: The concepts of shared information and consensus prevent possible losses due to fraud or embezzlement. In logistics-based industries, blockchain as a monitoring mechanism act to reduce costs.
• Security: Attacking a traditional database is the bringing down of a specific target. With the help of Distributed Ledger Technology, each party holds a copy of the original chain, so the system remains operative, even the large number of other nodes fall.
• Transparency: Changes to public blockchains are publicly viewable to everyone. This offers greater transparency, and all transactions are immutable.
• Collaboration: Allows parties to transact directly with each other without the need for mediating third parties.
• Decentralized: There are standards rules on how every node exchanges the blockchain information. This method ensures that all transactions are validated, and all valid transactions are added one by one.

Blockchain Versions

Blockchain 1.0: CryptoCurrency

The implementation of DLT (distributed ledger technology) led to its first and obvious application: cryptocurrencies. This allows financial transactions based on blockchain technology. It is used in currency and payments. Bitcoin is the most prominent example in this segment.

Blockchain 2.0: Smart Contracts

The new key concepts are Smart Contracts, small computer programs that "live" in the blockchain. They are free computer programs that execute automatically, and check conditions defined earlier like facilitation, verification or enforcement. It is used as a replacement for traditional contracts.

Blockchain 3.0: DApps

DApps is an abbreviation of decentralized application. It has their backend code running on a decentralized peer-to-peer network. A DApp can have frontend code and user interfaces written in any language that can make a call to its backend, like a traditional Apps.

Real-Life use case of Blockchain

Blockchain for Humanitarian Aid:

In January 2017 the united nations world food program started a project called humanitarian aid. The project was developed in rural areas of the Sindh region of Pakistan. By using the Blockchain technology, beneficiaries received money, food and all type of transactions are registered on a blockchain to ensure security and transparency of this process.


BlockChain Variants

Public:

In this type of blockchains, ledgers are visible to everyone on the internet. It allows anyone to verify and add a block of transactions to the blockchain. Public networks have incentives for people to join and free for use. Anyone can use a public blockchain network.

Private:

The private blockchain is within a single organization. It allows only specific people of the organization to verify and add transaction blocks. However, everyone on the internet is generally allowed to view.

What is Mining in BlockChain

Mining: Mining is the process of confirming transactions and adding them to a public ledger. To add a transaction to the ledger, the “miner” must solve an increasingly-complex computational problem (like a mathematical puzzle). Mining is open source so that anyone can confirm the transaction. The first “miner” to solve the puzzle adds a “block” of transactions to the ledger. The way in which transactions, blocks, and the public blockchain ledger work together ensure that no one individual can easily add or change a block at will. Once a block is added to the ledger, all correlating transactions are permanent, and they add a small transaction fee to the miner’s wallet (along with newly created coins). The mining process is what gives value to the coins and is known as a proof-of-work system.
---Knowledge acquired from various resources online and our take on this subject

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What Comes Under Big Data?

Big data involves the data produced by different devices and applications. Given below are some of the fields that come under the umbrella of Big Data.

• Black Box Data : It is a component of helicopter, airplanes, and jets, etc. It captures voices of the flight crew, recordings of microphones and earphones, and the performance information of the aircraft.
• Social Media Data : Social media such as Facebook and Twitter hold information and the views posted by millions of people across the globe.
• Stock Exchange Data : The stock exchange data holds information about the ‘buy’ and ‘sell’ decisions made on a share of different companies made by the customers.
• Power Grid Data : The power grid data holds information consumed by a particular node with respect to a base station.
• Transport Data : Transport data includes model, capacity, distance and availability of a vehicle.
• Search Engine Data : Search engines retrieve lots of data from different databases.

Thus Big Data includes huge volume, high velocity, and extensible variety of data. The data in it will be of three types.

• Structured data : Relational data.
• Semi Structured data : XML data.
• Unstructured data : Word, PDF, Text, Media Logs.

Benefits of Big Data

Big data is really critical to our life and its emerging as one of the most important technologies in modern world. Follow are just few benefits which are very much known to all of us:

• Using the information kept in the social network like Facebook, the marketing agencies are learning about the response for their campaigns, promotions, and other advertising mediums.
• Using the information in the social media like preferences and product perception of their consumers, product companies and retail organizations are planning their production.
• Using the data regarding the previous medical history of patients, hospitals are providing better and quick service.

Big Data Technologies

Big data technologies are important in providing more accurate analysis, which may lead to more concrete decision-making resulting in greater operational efficiencies, cost reductions, and reduced risks for the business.

To harness the power of big data, you would require an infrastructure that can manage and process huge volumes of structured and unstructured data in realtime and can protect data privacy and security.

There are various technologies in the market from different vendors including Amazon, IBM, Microsoft, etc., to handle big data. While looking into the technologies that handle big data, we examine the following two classes of technology:

Operational Big Data

This include systems like MongoDB that provide operational capabilities for real-time, interactive workloads where data is primarily captured and stored.

NoSQL Big Data systems are designed to take advantage of new cloud computing architectures that have emerged over the past decade to allow massive computations to be run inexpensively and efficiently. This makes operational big data workloads much easier to manage, cheaper, and faster to implement.

Some NoSQL systems can provide insights into patterns and trends based on real-time data with minimal coding and without the need for data scientists and additional infrastructure.

Analytical Big Data

This includes systems like Massively Parallel Processing (MPP) database systems and MapReduce that provide analytical capabilities for retrospective and complex analysis that may touch most or all of the data.

MapReduce provides a new method of analyzing data that is complementary to the capabilities provided by SQL, and a system based on MapReduce that can be scaled up from single servers to thousands of high and low end machines.

These two classes of technology are complementary and frequently deployed together.

Operational vs. Analytical Systems

	Operational	Analytical
Latency	1 ms - 100 ms	1 min - 100 min
Concurrency	1000 - 100,000	1 - 10
Access Pattern	Writes and Reads	Reads
Queries	Selective	Unselective
Data Scope	Operational	Retrospective
End User	Customer	Data Scientist
Technology	NoSQL	MapReduce, MPP Database

Big Data Challenges

The major challenges associated with big data are as follows:

• Capturing data
• Curation
• Storage
• Searching
• Sharing
• Transfer
• Analysis
• Presentation

To fulfill the above challenges, organizations normally take the help of enterprise servers.

HADOOP BIG DATA SIMPLIFIED

Today we live in the age of Big data, where data volumes have outgrown the storage & processing capabilities of a single machine, and the different types of data formats required to be analyzed has increased tremendously. 

This brings 2 fundamental challenges:

How to store and work with huge volumes & variety of data
How to analyze these vast data points & use it for competitive advantage.
Hadoop fills this gap by overcoming both challenges. Hadoop is based on research papers from Google & it was created by Doug Cutting, who named the framework after his son’s yellow stuffed toy elephant.

So What is Hadoop? It is a framework made up of:

HDFS – Hadoop distributed file system
Distributed computation tier using programming of MapReduce
Sits on the low-cost commodity servers connected together called Cluster
Consists of a Master Node or NameNode to control the processing
Data Nodes to store & process the data
JobTracker & TaskTracker to manage & monitor the jobs
Let us see why Hadoop has become so popular today.

Over last decade all the data computations were done by increasing the computing power of single machine by increasing the number of processors & increasing the RAM, but they had physical limitations.
As the data started growing beyond these capabilities, an alternative was required to handle the storage requirements of organizations like eBay (10 PB), Facebook (30 PB), Yahoo (170 PB), JPMC (150 PB)
With typical 75 MB/Sec disk data transfer rate it was impossible to process such huge data sets
Scalability was limited by physical size & no or limited fault tolerance
Additionally, various formats of data are being added to the organizations for analysis which is not possible with traditional databases
How Hadoop addresses these challenges:

Data is split into small blocks of 64 or 128MB and stored onto a minimum of 3 machines at a time to ensure data availability & reliability
Many machines are connected in a cluster work in parallel for faster crunching of data
If any one machine fails, the work is assigned to another automatically
MapReduce breaks complex tasks into smaller chunks to be executed in parallel
Benefits of using Hadoop as a Big data platform are:

Cheap storage – commodity servers to decrease the cost per terabyte
Virtually unlimited scalability – new nodes can be added without any changes to existing data providing the ability to process any amount of data with no archiving necessary
Speed of processing – tremendous parallel processing to reduce processing time
Flexibility – schema less, can store any data format – structured & unstructured (audio, video, texts, csv, pdf, images, logs, clickstream data, social media)
Fault tolerant – any node failure is covered by another node automatically
Later multiple products & components are added to Hadoop so it is now called an eco-system, such as:

Hive – SQL like interface
Pig – data management language, like commercial tools AbInitio, Informatica,
HBase – column oriented database on top of HDFS
Flume – real time data streaming such as credit card transaction, videos
Sqoop – SQL interface to RDBMS and HDFS
Zookeeper – a DBA management for Hadoop
And several such products are getting added all the time from various companies like Cloudera, Hortonworks, Yahoo etc.

How some of the world leaders are using Hadoop:
Chevron collects large amounts of seismic data to find where they can get more resources
JPMC uses it for storing more than 150 PB of data, over 3.5 Billion user log-ins for Fraud detection
eBay using it for real time analysis and search of 9 PB data with 97 million active buyers, over 200 million items on sale
Nokia uses it store data from phone service logs to analyze how people interact with apps and usage patterns
Walmart uses it to analyze customer behaviour of over 200 million customer visits in a week
UC Irvine Health hospitals are storing 9 million patients records over 22 years to build patients surveillance algorithms
Hadoop may not replace the existing data warehouses, but it is becoming the number 1 choice for Big data platforms with a strong price/performance ratio. Best Computer Training Institute

The Right Skills for the Job?

                          

Best Computer Training Institute Creating jobs and increasing productivity are at the top of agenda for policymakers across the world. Knowledge accumulation and skills are recognized as central in this process. More-educated workers not only have better employment opportunities, earn more, and have more stable and rewarding jobs, but also they are more adaptable and mobile. Workers who acquire more skills also make other workers and capital more productive and, within the firm, they facilitate the adaptation, adoption, and ultimately invention of new technologies. This is crucial to enable economic diversification, productivity growth, and ultimately raise the standards of living of the population. :)

New ideas on how to build and upgrade job relevant skills, focusing on three types of training programs relevant for individuals who are leaving the formal general schooling system or are already in the labor market: 

1. pre-employment technical and vocational education and training (TVET); 
2. on-the-job training (OJT); and 
3. training-related active labor market programs (ALMPs). 

Several previous studies have discussed some of the flaws in current systems and outlined options for reform. As a consequence, there has been a shift away from the investment in pre-vocational training courses to programs to improve access to and the quality of general secondary education. There have also been calls to encourage a stronger involvement of the private sector in the provision of training, together with increased emphasis in the quality and relevance of the content. One result has been a push to rethink the governance and financing arrangements of training institutions. But overall policies at these three levels of the training systems remain disconnected and there has not been an integrated framework linking them to the market and government failures that need to be addressed. This book makes two important contributions. First, it takes an in-depth look at the types of market and government failures that can result in underinvestment in training or the supply of skills that are not immediately relevant to the labor market. Second, building on the analysis of the limitations of both markets and governments and the results of case studies and recent impact evaluations, the report develops new ideas to improve the design and performance of current training systems.