MSBI # 72 – BI # 5 – Big Data # 2 – What is Big Data ? What is No SQL ? What is Relation in association of Microsoft with SQL Azure , Windows Azure ,Big Data and No SQL together
Lets brush-up’s some knowledge related to all topics which are in the header of this post which was started way back but now there is real need to understand and implement it.
In one of the previous post I have tried explaining relation between Hadoop and Big Data, if you have missed it following is the link
We do have some of older post on Azure as follows :
- My First Day …Lets Start with Windows Azure !!
- Windows Azure Overview,Lifecycle,Storage,Security,Elasticity and from Start to end !!!!!
So now here we can again go with some terminology related to all rocket words for most of us now, which are nothing but Big Data, NoSQL and its Relation in association of Microsoft with SQL Azure, Windows Azure, Big Data and No SQL together !
In this post we surely have clear idea about BIG DATA at the end ..
In this article we are going to cover simpler topics such as
- What is Big Data ?
- Big Data in all Direction ?
- What is SQL Azure ?
- What is Windows Azure ?
- What is Relation between SQL Azure , Windows Azure and Big Data
- What is NoSQL ?
Lets understand one by one !$!
What is Big Data ?
Consider a scenario where we haver our application running and we are getting data from different Data Source on premises , But as we know Data is getting larger and larger we move that on to cloud like azure – This Data is Called Big Data.
Big Data is where you can take data sets that are large and that are also meaningful but have not traditionally been put together, to find new meaning. Success in the Big Data era is about more than size. It’s about getting insight from these multiple, data sets more quickly.
Big Data in All Direction
Some of easy answer and future of Big Data and its various ways as follows
- Big data is made up of data sets that grow so huge that they become difficult and clumsy to work with using on-hand data management tools.
- That’s about statistical analysis at scale and tools to split the work between various computers, as it isn’t possible anymore to process on a single server.
- Big data will continue to get a lot of attention in the news, as this problem will grow.
- Big Data is a buzz word that is directly correlated with new techniques being used to handle large datasets that may be heterogeneous in nature. Processing this data may require a parallelized processing so that it does not take days or years.
- To understand Big Data we must first appreciate that there’s been an explosion in the amount of data available. There’s been more data produced in the last 3 years than the rest of human history. 1 Zettabyte – 1 trillion (million, million) gigabytes – rising by a factor of 44 to 35 zbs by 2020. There’s also been an explosion, not just in the size but the methods for correlating, analysing and leveraging that data.
- It’s not just more streams of data, but entirely new ones. For example, there are now countless digital sensors worldwide in industrial equipment, automobiles, electrical meters and shipping crates.
- New approaches have developed to deal with this deluge of data. So Facebook has to manage all of its users, all of their interaction and also 40 billion photographs. Decoding the human genome involves analysing 3 billion base pairs—which took ten years the first time it was done, in 2003, but can now be achieved in one week. Other firms face similar challenges to control and exploit huge amounts of data; Google, Twitter, Tesco’s, NASA, Disney, Wall-Mart, Barnes and Noble, Flight Caster, LinkedIn etc.
- This leaves us with questions. If only we could formulate the right questions. If only we could devise the right sampling strategies. If only we had big enough machines to ask lots of questions using lots of sampling strategies. If only we had big enough machines to not bother sampling at all. This requires a dramatic shift due to increased speed of processing, scaling of technology and data systems.
- An example of "big data" is databases needed by social media sites like LinkedIn. The amount of data generated from sites like this is huge and creates unique challenges for both software and hardware. Each user uploads a large amount of content that must be stored, sorted, searched and shared
- This term refers to advancing trends in technology that open the door to a new approach to understanding the world and making decisions. There is a lot more data, all the time, growing at 50 per cent a year, or more than doubling every two years, estimates IDC.
- They can measure and communicate location, movement, vibration, temperature, humidity, even chemical changes in the air.
- “Big Data” is a catch phrase indeed that is overstretched, and as such is becoming less and less meaningful.
- What it (used to) mean is that you have more and more digital information available, and need new tools to make sense of them, to find the signal in the noise.
- One of the technique Google pioneered is map reduce, where a task is distributed among a cluster of servers where each work on part of the data, and then putting all the partial results together at the end .
- On the storage front, the nosql movement is aiming at making it easier to split the data on several computers, and work in parallel on this cluster. This is what we mean by Big Data.
What is SQL Azure ?
SQL Azure is a highly available and scalable cloud database service built on SQL Server technologies. With SQL Azure, developers do not have to install, setup or manage any database. High availability and fault tolerance is built-in and no physical administration is required. SQL Azure is a managed service that is operated by Microsoft and has a 99.9% monthly SLA.
SQL Azure provides a full featured relational database and enables many different types of applications. Some common scenarios include:
- Business applications
- Hybrid applications
- Business intelligence
Following are some Capabilities and Benefits of SQL Azure
- No physical administration required
- Scale On-Demand
- Innovate faster
What is Windows Azure ?
Windows Azure is an open and flexible cloud platform that enables you to quickly build, deploy and manage applications across a global network of Microsoft-managed datacentres. You can build applications using any language, tool or framework. And you can integrate your public cloud applications with your existing IT environment.
Following are some key features :
- Always up. Always on.
- Open (Any language)
- Unlimited servers. Unlimited storage.
- Powerful Capabilities
- Quick-start of any Business Analytics
- Seasonal processing
- Deployment choices
What is NoSQL ?
Make a note NoSQL is not No (X) SQL but more over it’s Not only Only SQL
Which is nothing but unstructured, unspecified , DE normalized and Non Relational Dump of Data.
What Relation between Windows Azure and SQL Azure
In following diagram we can see relation ..
What is Relation between SQL Azure , Windows Azure and Big Data !!
Windows Azure Data Storage
Unstructured data storage
Semi-structured or tabular data storage
Buffered delivery data storage
Durable NTFS volumes that Windows Azure applications can use.
– Relational data storage
Relation between SQL Azure , Windows Azure and Big Data :
CAP Theory :
- Consistency means that each client always has the same view of the data.
- Availability means that all clients can always read and write.
- Partition tolerance means that the system works well across physical network partitions.
- CAP theorem says you choose 2 from CAP attributes. The above diagram tells how this attributes apply across some of the NoSQL Providers
So in summery SQL Azure and Windows Azure are best featured platform for Big Data
Hope you will like this post on What is Big Data ? What is No SQL ? What is Relation in association of Microsoft with SQL Azure , Windows Azure ,Big Data and No SQL together.
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