What is Big Data?
Big data is large amounts of data that are found in a system in three forms:
- Stored Data
- Streamed Data
- Manipulated Data
Large quantities of data found in storage, usually in databases, combine with incoming and outgoing data streams providing constantly updated databases. These streams of data are usually manipulated to provide information that is reached through the processing of the data in a number of processes.
Big data requires four physical property characteristics:
- Large storage drives
- Large memory banks
- Powerful processing power configurations
- Wide bandwidth
The storage has to be sufficient to provide both physical storage and physical memory manipulation. The memory units must also be able to provide both physical, and virtual memory capabilities, and the processing powers from CPUs and systems combined to leverage the most out of a system had to be sufficiently large and cooled to allow constant and safe data process. Add to this a backup of the data sets; you need more than double the amount of physical storage than the database would usually require.
Streaming and Processing
Data streaming requires wide bandwidths, even more so big data, especially within and between systems. The processing power is enhanced when data is manipulated efficiently within a system. As a note to this article, blockchain as a decentralized platform approaches the processing of big data by assuring that there are multiple nodes of equal data sets all over the globe, which inherently creates a super-computer for processing. The downside of blockchain is that all the nodes have to be synced, so processing is slowed down due to security issues, which is the only real issue of blockchain as a big data processing option.
Big Data Manipulation
There are many companies providing big data manipulation as a service. This means that they provide both the physical systems and the software to handle large sets of data. Software managing large data has to be able to manage memory in an optimized fashion since speed is one of the issues when handling large databases of information.
One of the most important concepts that big data services now face is how to provide a decision-making solution in real-time speed. Something that SAP Hana has tried to accomplish by changing the entire structure of how data is manipulated in a database.
Other service providers concentrate on optimized processing solutions, or what is termed software as a solution (SaaS).
Big Data benefits
Managing big data has its benefits, and these are most obviously seen in online e-commerce, finance, insurance, and healthcare systems. Large e-commerce sites are all about image and data with online sales solutions providing an immediate response to millions of users simultaneously. The data from these sales is then analyzed for trends and habits, and this is then in turn statistically analyzed for improved advertising and define which products are more profitable than others.
Search engine analytics, such as Google, require the use of big data analysis to update their “intelligent” algorithm for constant informatics constantly.
Hospitals manage large datasets for patients including clinical, diagnostic, and surgical information, all being manipulated per patient and analyzed against resource spending. Pharmaceutical companies manage large data sets from multi-site clinical trials.
Banking and finance manage extremely large data sets of information, with a constant flow of data through online sales, credit cards, ATMs’ transactions, stock and share trading, commodity trading, lending, other commercial activities, and digital currency trading.
Insurance companies maintain extremely large data sets of information per insured and have the most extensive datasets around, that link entire families to the 5th degree. Essentially, insurance company data sets could be considered the largest in the world due to the detailed amount of information that goes beyond medical files.
Innovations in Big Data Management
There are a few big data consulting services that provide a comprehensive solution to managing, analyzing, and reporting. Here is a look at a few to get an idea of what big data services are.
Kafka – Big Data Messaging
This is an Apache tool. The service is a subscription-based one that gives access to a platform for fast management of big data sets. It comes with asynchronous messaging that works on the basis of large data sets and according to LinkedIn Kafka claims it has reached 1 trillion events a day. This boils down to providing a large messaging service for big data sets and is applicable to companies that don’t have the necessary hardware and bandwidth to perform this function.
Cloudera – Hadoop
Cloudera is a Hadoop software manipulator. Hadoop is an Apache software library and provides the framework for the distribution of processing large data sets across clusters of computers via simple programming models. It is a decentralized platform that scales up from a single server to thousands of machines, each providing local computation, and storage. Cloudera uses Hadoop in an ingenious way; it acts as a comprehensive console that supports the Node Template feature. This way, Cloudera lets you create a template and re-use it to create more nodes. This speeds up the Hadoop processing exponentially.
Splunk is a big data analysis and aggregator tool that can work with big data sets, providing real-time results. It is usually found in many application management, security, and compliance system. Set to report log irregularities for immediate response.
This is a search engine for reading large data sets immediately, which provides large organizations the ability to find a specific string or word within a large database in near to immediate time. Another feature is its ability to work on a multi-tenant system, where different platforms are used to manage data.
SAP HANA is an in-memory, column-oriented, relational database management system. The structure of databases has always been rows. SAP changed the structure as well as the memory management, where it uses virtual memory to manipulate data sets for immediate processing and reporting. Essentially SAP HANA is a comprehensive cloud-based strategy solution that provides physical storage, memory, and bandwidth to manipulate big data up to 10 times faster than its competitors.
Sine big data management is a service, as most companies will not go to the expense of investing in highly complex big data management (CAPEX) solutions. A lot of companies are starting to emerge providing access to Cloud-based bug data management services for focused requirements. Analytics is as important as data handling, and the analytic end of these services is what is attracting the attention of companies as much as the offered storage and backup requirements.