Cloud Big Data Technologies-Cloud Computing

Here you will get a detailed information about cloud big data technologies. This is very important to know if you are having a buissness with huge data or big data. Aspiring Data Scientist also must read this in order to get the proper knowledge about Cloud Big Data Technologies. Moreover, everyone who are coming digitally should know about this, Cloud Big Data Technologies as it is going to replace the traditional means of storing Data. Here you will Read about :

1) What is Big Data ?

2) What are Cloud Big Data Technologies ?

3) Is it really worth of Cloud Big Data Computing ?

4) What are Customers asking for Cloud Big Data Technologies ?

5) What is the Role of Microsoft in Cloud Big Data Technologies ?

Now let's start with the basics before going deep in Cloud Big Data Technologies...

What is Meant by Cloud in "Cloud Big Data Technologies" ?

In this digital world, Cloud means a dedicated server in the internet where data is stored. I mean where Big Data is stored. The brief definition of big data is mentioned below. If a company is storing data in dedicated Clouds that means that its employees can easily access the Required Data for their work without the risk of Data Theft or some other problems. This Cloud Big Data Technology is playing a very vital role in computing the data in big companies.

What is Big Data ?

Data, there’s so much of it that even the term Big Data doesn’t seem to describe it accurately. It feels more like Huge Data, or Gigantic Data, right? To make Big Data less abstract, it can help to break it into four dimensions of which the sheer amount of data is just one aspect. The others are types of data: videos, photos, texts, structured data in spreadsheets, you name it.  

Then there is the speed at which all this data can be processed. And finally, there is the reliability of data. Together, these dimensions also determine the value of data.  Companies and individuals can be flooded by data. One drop of data is pretty useless.  But when you collect a bucket or even an ocean of data you can start to see patterns that may lead to useful insights. 

But as we’ve said before, the value of data is not in having a lot of it. You need to use the right data.  Using that data intelligently can make a huge difference in the world. 

Here is an Example to understand Big Data :

In the most popular sport on the planet, for instance, Football. More and more clubs use big data to gather statistics on the players: their top speed, the distance they run in a match, the accuracy of their shots.

The next step is analyzing this data. That is where analytics tools come in they can help you make sense of the huge amounts of data and allow data to be transformed into insights. Information that can help coaches to come up with personalized training programs  and optimal game strategies or scouts with selecting the most promising talents. With predictive analysis it’s even possible to predict what is going to happen. 

Is making Cloud Big Data technology or computing Really Worth ?

Finally, the data can be made available to others, like the fans.  Making data available beyond your own organization is known as Data Intelligence. For companies, rather than football clubs, Data Intelligence offers the possibility to aggregate  and anonymize data to be made available to a wider community. 

The challenge is no longer how to harvest it, but how to use it in smart ways.

Big data Cloud Computing or Could Big Data Technologies :

There are three major trends that are happening in the data space. 

One of them is Big Data and IoT.

The second one is Cloud and the third one is Intelligence. And all of three of these trends are converging on the data management solution for analytics like it hasn't before. And so let's talk about this.


Specifically, we are in a world of connected data. And so it's a lot different than it was in the 90s, or even in the early 2000s. The data is not just structured relational tables anymore. Now it includes data from different sources, from connected and IoT devices and from digital devices. And so, data has been exploding. In fact, we'll see more about this in the future part of this session. Let's talk about data as a key strategic asset. 

So data certainly seem as a key strategic asset. We all know this. A lot of us, as we think about data investments, know this. But we know that there are also inherent challenges to the way we currently manage your data for analytics today. And some of these challenges are that the data characteristics have essentially changed.

Instead , the data that's being stored in relational format only, it's now changing to include non-relational data, as well as data that's increasing in volume such that analyst companies like IDC has seen that or predicted that, data will grow to 44 zettabytes by 2020, and so data is certainly growing faster than we can keep track of it. 

The other challenges that all are facing is always this trade-off between performance and price, and so often times we want more performance but we also don't want to pay the increasing price that's associated with it. 

The third challenge is around fragmented architectures. Now and now, it's not just a single offering that's on premises, with the Cloud you have to think about hybrid scenarios as well as incorporating open source technology as part of your solution. And so, there's fragmentation all over the place as it relates to your architecture.

And the final challenge is the need to support new audiences and have new insights, so no longer is it just your traditional business analyst writing operational reports, but you also have to be able to accommodate data scientists who are running experimentation, or even developers who are doing intelligent applications and may need access to data and so for sure as a technology leader we need to incorporate all of these different new types of audiences. 

And so what we need, is a single solution, a data management platform for analytics, something that can take in relational data as well as non-relational data. Be able to abstract the complexities of that data so that you can do either type of processing, either data warehousing or big data analytics, and make that available across any BI tool, any advanced analytics solution andany language, and finally make that available both on-premises and in the Cloud. 

What are Customers asking in Cloud Big Data Technologies ?

And so this is what  customers have been asking for and something that Microsoft has been offering. And so, before talking about Microsoft offering. I do wanna mention that Microsoft is uniquely able to understand this specific solution because they have done it before. 

Role of Microsoft in Cloud Big Data Technologies : 

Within Microsoft, they have been addressing this challenge for the last ten years without our own internal solution. In fact Microsoft is running one of the largest big data implementations in the world today. Supporting 10,000 developers in exabytes of data under management. And so what is a solution that we have for you? 

Microsoft has a complete end-to-end,data management platform for analytics that includes relational investments, like on SQL Server, as well as their big data investments,such as HD insight and Azure data league and we provide this over on-premises and in the Cloud and Hybrid Solutions. 

So i have a complete solution for you and so if you haven't looked at Microsoft recently, we certainly invite you to look at their SQL Server solutions on-premises. As well as all of their big data and advanced analytics solutions as a part of the Cortana Intelligence Suite in the Cloud.

 And these solutions collectively can en capsulate your relational and your non-relational data. Be able to abstract the complexities from your end user and be able to do any sort of processing on top of it with any type of tool or solution, or advanced analytics tool that you have to gain dramatic insights. 

And so the question that you have to ask yourself now is, 

Where are you ? 

What stage of your data investment are you on ? 

Are you currently implementing a traditional data warehouse ? 

Are you doing operational warehouses where you're gaining real-time insights without impacting the performance ?

 And as you step upwards,are you now incorporating big data as part of your data warehouse as a logical solution ? Or a free form solution of where you're doing advanced analytics and deep learning on top of your data. 

Where are you as part of this stage ? And that will help you understand what you have to do next as part of your solution. So these should be our next steps. 

The first one is that Microsoft is offering an exclusive full month trial for Azure SQL Data Warehouse. So you must try this to know better about Cloud Big data technologies.