According to Gartner describes it "Big Data is high-volume, high-speed or high-quality information resources that demand new ways of processing to facilitate enhanced decisions insights, insight discovery, and process optimization. "Let's look deeper into the subject and learn about this concept in a simpler way.
The term "big data" is self-explanatory. It is a collection of massive data sets that standard computing methods are not able to process. The term does not just refer to the data itself, as well as the many tools, frameworks and methods that are involved. Technology advancement and the introduction of new communication channels (like social networks) and the development of new, more powerful devices have created a problem for industry players in that they must find alternative ways of handling the massive amount of data.
Since the dawn of time until 2003, the globe had only 5 billion gigabytes worth of information. Similar amounts of information were created within two days 2011. In 2013, this amount was being generated every 10 minutes. Therefore, it is not surprising that the generation of 90% of data on the planet is happening in the last few years.
All of this data is valuable when it is processed, but it was in complete disregard before the idea that big data became popular.
As you've understood about Big Data, let's get to know the origin for Big Data.
Why Big Data?
With the rise and development of social media and apps and the movement of people and companies online There's been a massive rise in the amount of data. When we consider only social media sites that are popular, they attract millions of users each day and are able to scale up data faster than they ever have. The next question is how do you handle this massive volume of data dealt with and handled and stored. This is the point where Big Data comes into play.
Additionally, Big Data analytics has revolutionized the field of IT improving and adding an added benefit to companies. It is the application of analytics, the latest technologies such as machine learning mining, statistics, and much more. Big data is a great way for teams and companies to execute several operations on a single platform. It can store Tbs of data, process it and analyze the entire data, regardless of size or type and also visualize it.
The Sources of Big Data
Black Box Data
It is the data produced by helicopters and jets. Black box data include voice recordings of flight crews as well as microphone recordings and details about the performance of the aircraft.
Social Media Data
The data is gathered by the social media platforms such like Twitter, Facebook, Instagram, Pinterest, and Google+.
Stock Exchange Data
This information comes obtained from stock exchanges regarding the buying and selling choices made by the customers.
Power Grid Data
These are data that comes from power grids. It is a repository of information for specific nodes, like the information about usage.
This can include the capacity of the vehicle and vehicle models availability, and the distance traveled by a car.
Search Engine Data
This is among the biggest sources of large data. Search engines have massive databases that they use to collect their information.
In addition, Bernard Marr, a Big Data and Analytics expert has also come up with his amazing listing of the top 20 Big Data sources that are open to anyone on the internet. A few of them are detailed on this page.
Data.gov - where all US Government data is accessible for free and all information from crime to climate data is readily available.
Similar to this is similar to UK Govt. site, Data.gov.uk, where the metadata of all UK publications and books since 1950 can be collected.
Additionally, there is an agency - the US Census Bureau which provides important information such as population, geography as well as other data. Similar to this can be found similar to the European Union Open Data Portal that includes census data of European Union institutions.
In addition, something that is more in line with our needs and our interests - The Facebook Graph is a service that provides the information for the application program interface (Graph API) after obtaining information from all data which is made public by Facebook users.
Google Trends, Google Finance, Amazon Web Services public datasets are all similar examples. Based on these examples it is evident that big data isn't just about volume. It also has a large range of data. The year 2001 was the first time Doug Laney - an analyst in the industry - defined the three variables of data: volume, velocity, and the variety.
The rate at which data is being streamed is unimaginable, which makes it challenging to handle the data in a timely manner. Smart metering, sensors and RFID tags are required to handle data streams in real-time. The majority of businesses are having a hard time to quickly respond to data.
In the past the issue of having too much data was a simple storage issue. With the increase in storage capacity and less expensive storage companies like Remote DBA Support are now focused on how data that is relevant can bring value.
There's a greater range of data available today than it was just in the past. Data can be generally classified into three categories: classified as structured information (relational data) as well as semi-structured information (data that is in XML sheets) as well as unstructured information (media logs as well as data in the format that are PDF files, Word, and Text files). A lot of companies are faced with managing, governing, and integrating the various types of data.
The quality of data, veracity (the high-quality of data) and variation (the inconsistent data that sometimes shows) and the complicated (when dealing with huge amounts of data from multiple sources) are the other key aspects of data.
After understanding the concept of Big Data, and its sources, we have to learn the advantages from Big Data to become a Big Data Engineer.
Advantages of Big Data
The consumer of today is very demanding. He interacts with other people on social media, and also looks at different options before making a purchase. The customer would like the attention of an individual, and to be praised after purchasing an item. Big data means you'll get data that's actionable which you can utilize to interact with your customers in real-time. One of the ways big data can allow you to achieve this is to be able check the profile of a customer who is complaining in real time and find out information about the product or service he/she is expressing complaints about. Then, you will be able to conduct reputation management.
Big data can help you develop new products or services that you offer. The information on what people think about your products, for example by way of unstructured social network site content- aids you with product development.
Big data lets you experiment with various versions in images using CAD (computer-aided design) images to assess the impact of minor changes on your product or process. This is why big data can be extremely valuable for manufacturing processes.
Predictive analysis can keep you ahead of your competition. Big data can assist in this, for example, by analyzing and reading the feeds of social media and newspaper reports. Big data can also help you perform health checks on your clients suppliers, customers, and other stakeholders to help minimize risks, such as default.
Big data is helpful in keeping data safe. Big data tools allow you to visualize the data landscape of your business, which aids in the evaluation of internal security threats. For instance, you can determine whether your personal information is protected security or not. An additional example is that you'll be able to identify the sending or storage of 16-digit numbers (which could, in the future include credit card number).
Big data lets you increase the number of revenue streams you can earn. Big data analysis can provide you trends-based data that can aid you in creating an entirely new revenue stream.
Your site must be up-to-date if you want to be competitive in the highly competitive online market. The analysis of large data can help to personalize the appearance, content and experience of your website to meet the needs of each visitor by analyzing, for instance the nationality, sex and even their nationality. One example could be the Amazon's IBCF (item-based collaboration filtering) which powers the "People you may know" and "Frequently bought together" features.
If you run in a factory, the big data is essential because you don't need to replace technology pieces according to the length of time or years they've been in operation. This is expensive and unpractical as different parts wear at different rate. Big data lets you detect failing devices and identify when you need to replace them.
The use of big data has become crucial within the medical industry that is among the few industries that are using a generalized, traditional approach. For instance, if you are diagnosed with cancer, you'll undergo a single treatment and if that doesn't perform, your physician will suggest a different treatment. Big data allows cancer patient to be treated with a medication that is formulated in accordance with their genetic.
Challenges of Big Data
One of the challenges that Big Data faces is the huge increase in raw data. Data centers and databases contain vast amounts of data which is rapidly growing. Due to the rapid increase in data, businesses frequently struggle to properly store the data.
The next task is deciding on the appropriate Big Data tool. There are a variety of big Data tools but picking the wrong one could cause waste of time, effort and money.
The next issue with Big Data is securing it. Many organizations are so busy studying and analyzing data, that they forget about the security of data for an undetermined time and, if they do not secure data, it can become a fertile ground for hackers.