A large volume of data is termed as big data. It is usually available in structured as well as unstructured forms. An organization or any business needs to deal with such data on a day to day basis. Every company analyses big data for better decision making within the organization. The process is known as big data analysis. It is also the combination of semi-structured, unstructured, and the structured data usually collected by organizations and apply for the information among the projects which are machine learning in nature. Various systems automatically process the relevant data that is stored. This practice has become quite common for data management within an organization.
History of Big Data
Most of you must have a question in your mind on ‘what is big data? ’ The concept became quite popular in 2005. The term big data not only means large data collection. Rather, the big data capabilities are known for its fast as well as complex nature. Processing of it may not be possible with the traditional method. Indeed, the method of having access and storing of data within the organization was there for a decade and more. But, there were no many proven facts as well as the theories associated with the same. Then the eminent analyst of the industry Doug Laney defined big data with three V’s. Yes, those are:
1. Volume- Here, the organization adopts the practice of collecting data from several sources. Those include videos, smart devices, business transactions, society, etc. There was a time when storing such data has been a problem. But, today with the big data Hadoop this has become quite easy.
2. Velocity- As we land on the edge of the internet, the speed has become an important consideration. Thus, the big data speedily passes to the business. Also, there is a requirement that those must be handled on time. The smart meters, RFID tags, sensors, etc are making the needs to catch up its real-time.
3. Variety- The third ‘V’ is not other than the variety. The Data so collection comes in different formats as well as types. Those include numeric data, structured as well as the traditional database. These also include big data initiatives in the form of video, audios, documents, financial transactions, etc.
Big data analytics
Few people may have a very faint idea about the big data as well as its analytics. It is the system of using advanced analytics that stands against data sets, diverse data. Big data analytics also includes information about the structured, unstructured as well as semi-structured data. This may have different sizes and derives from several sources. The sizes may vary from terabytes to zettabytes. This also has a connection with the data processing and data visualization. Finding the appropriate data point is also important to get the appropriate big data analytics. These are applied to those areas where the capability of data processing is quite low.
The big data analytics systems are mostly derived from the data analysis procedure. To get the enriched data it is very important to go ahead with factors like Artificial Intelligence (AI), high velocity, networks, log files, devices, audio/video, etc. All these are widely generated on a very large scale and in real-time. Within the data systems, the generated data are collected in batches. The data analysts of the big data make the decision of data much more effective. Data sets are also used with the data integration method. The data that was previously inaccessible or unusual can now be easily accessed with the help of big data. The organization can also use the cognitive big data through this big data application. It is also possible to get new insights from the previously untapped data.
Importance of big data
The importance and usability of big data do not revolve around the fact on the volume of data you have. Rather, the utilization of the entire bunch of data becomes quite important over here with the big data technology. From the entire system, you can easily get data from any source. After the data collection, you can easily analyze the same as much as you can. Thereafter you can easily find the answer with big data technology. There was a time when the data collection took place. But, those were not effectively done due to improper knowhow and the infrastructure with associated implementation. But today, the collection is done from the right data source. Also, there exist no flaws while sourcing the same. Also, the entire process has the following benefits:
1. It does the task in very less time
2. The cost is reduced as well
3. Development of new products with big data analytics applications
4. The capacity of smart decision making with the center of excellence
Also, for every business, big data will initiate smart decision-making capacity. It gets the correlation between high powered analytics. But, there are certain risk factors in every business. The big data strategy can find out the root cause of failures in every business. The defects that an organization is having in real-time will be found out with the big data solution. You must have observed that in much organization, the coupons are generated for getting the reduced price of the product which the individual buy. It is through the data analysts that the deserving customers are discovered. With the center of excellence, it is also possible in recalculating the total risk portfolio in minutes. With perfect data management, you can easily protect your organization before it affects your company with fraudulent activity. Some scientific methods are also used in many places.
Most companies start with a big data preparation process. Then those are accumulated within their system to get the operations improved. The modern data integration takes place within this system. As a result, a personalized marketing campaign takes place with better customer service. The processing power of the company increases with information technology. The data storage of a company with a thorough understanding increases the profitability of a business. There is always a competitive advantage of the business and companies that deal with big data storage. Yes, they can easily make much more informed and faster business decisions with the impact factor. But, there is something that becomes mandatory. One needs to have proper utilization of data and gets its effectiveness as well. Data visualization is another important consideration.
With the help of big data, companies can easily get valuable insights. This also comes with the cloud interface which acts as the data warehouses. The valuable insights are what the big data provide to every company. Thus, the technique of marketing and product promotion will not be like the traditional and old style. The new and advanced big data-based models are refined marketing campaigns. As a result, customer engagement will be increased. This will bring out the highest conversion rates with the help of application software. Several big data research projects are having its peak time.
Customer-centric with big data
Every organization wishes to earn a profit. This is not possible without adequate customer or the client’s footfalls. The structured data within the organization will help in the successful implementation of a customer-centric attitude. The preferences of the customers are always important for every organization. The data sharing within the big data research projects will also include real-time data as well as the historical data of the customers. Thus, the business will easily get boosted with its marketing strategy. The method of processing work is very effective.
Big data for the health industry
Only the industry that concentrates on buying and selling goods is not the only place for big data. The open data also have additional technologies that are used by the researchers in the health industry. They go ahead with the predictive analytics to identify the disease and the risk factor within a patient. The big data holders are very useful to the doctors. They can easily diagnose the illness as well as diseases of the patient. Most of the data derived from electronic health records (EHRs) are based on system dynamics. Other sources of data driving include web, social media, etc. Large data sets are extracted in the health sector. The intelligent tools must be used to get information about the minute details on the disease and the threats associated with the same. Mass surveillance is used to protect the same. The big data based on analytics platform work pretty well.
Big data in the energy industry
The whole world is consuming unlimited energy each minute and seconds through several sources. The oil and gas companies must get a proper scope to work with the proper data and infrastructure. The big data flow within such industries is flawless. The complex data is also processed with the help of intelligent tools to efficiently manage the energy industry. With the help of big data systems, the company identifies the potential drilling location. The digital trace also helps in monitoring the pipeline operation. It also is used to get a proper track of the electrical grids. Information management is also a vital part of the energy supply industries.
Live big data
There are varied different sources from where the big data is accumulated. Some of the examples include the internet clickstream logs, customer database, scientific research repository, medical records, real-time data, machine-generated data, social networks. The sensor data is also available in this connection. The data collection transparency is again a vital fact. Within the big data system, it is quite likely that data can be available in the pre-processed form. One of the variations is known as the Topological data analysis program. This program has been tested and found out as a successful process in discovering information. This can vary from large as well as varied data sets. This has soon become an effective methodology. One of the reasons behind it is the fact that the data has a shape. According to the experts in this field, the shape matters.
The individuals dealing with data and have digital skills can make the process much more effective.
Comparative analysis of Data
Once the data are with you, it is very important to go ahead with the comparative analysis of the same. Customer satisfaction in real-time is something that you must always dream about. The big data will go ahead with the product and services based on this. The major role of this technique includes the examination of user behavior metrics. The next step will be to observe the same to check out real-time customer engagement. The unstructured data is also figured out over here and indulges in the comparative analysis of data. Thereafter the product and services of the particular brand are compared with that of its competitors.
Use of social media
These days’ maximum people are inclined towards social media. They share several facts and also see and listen to several posts on social media. If a business representative keeps an eye on social media, it will be very easy for him to extract the opinion that the mass has on the product and services of the said company. Through the survey as well as contents organized in social media it will be quite easy to get the data pools. This data can be easily used in marketing campaigns to get the target audience.
Analysis of market
Not all products and services belonging to all the companies are popular in the market. Thus, it is very important to find out the demand for the same among the people. After getting the right feedback from the customers it will be quite easy to make the best idea on the demand for products in the market. This will include the promotion of new products, services as well as innovations to get more informed and popular products. The analytical processes are used over here as well.
Customer satisfaction
This is one of the important techniques of the marketing practices taken place in the modern set. Here, the sentiments and the viewpoint of the customer are given more value than the sale of the products and services in the market. Through the internet of things, the information is gathered. Data scientists are then approached for further processing. Through this, it will be quite easy to find out about what exactly the customers are feeling about the products and services about the company. This can be found out in real-time. All the issues of the customers are addressed in such a way that the customer does not have a hard feeling about the company and the people working in it.
Characteristics of big data
- There are several characteristics of big data in which an individual did not have an idea. The perfect decision making in a business environment is a vital concern. The data veracity comes among 3 V’s. This is the term used for the degree of assurance in data sets. This can be used in vast amounts. This helps in getting operational efficiency on a large scale. There are also some uncertain raw data that an organization collects from unreliable sources such as several Webpages and social media sites. This will, however, cause a severe problem with the data quality. The data extracted with the use of mobile devices are quite common. But, are they truly reliable? The big data policing will be effective with the digital transformation.
- If you get bad data from the sources, the analysis will be wrong. This will easily undermine business analytics as well. As a result, the employees working within the organization will be unable to trust the data so provided. Thus, the best thing to do in such a situation is to count the uncertain amount of data. The accountability must be done before it is used in the big data application. The proper resource management for better customer experience. The experts in IT, as well as analytics teams working within the organization, must ensure with good quality of data so that they can produce a valid result. The open-source of data is used as well.
- Big data is also used in biomedical research centers. The scientists also add value to the characteristics of big data. There must be an effective correlation between the science group with experts dealing with the process of business intelligence. Data is collected in a large amount from various sources. But it will be wrong to think that all the data that is brought are useful. Rather, they don’t have a real business value. The negative impact of such data can weaken the insight as provided by the analytics application. There are several other practices that an organization practices to overcome from such a situation. This includes data cleansing. Thereafter the experts confirm that the data are related to the particular business. This must be effectively done before it is going to be used for big data analytics projects.
- Another important characteristic of big data is the fact of variability. This is less consistent as compared to the conventional transaction data. This also may have multiple meanings. The data mining activity is quite popular over here. Also, the procedure of formatting the same will be in several different ways. The factors are quite easy to make the process much more complicated. It becomes really hard to process as well as analyze such data. The method of parallel processing is something which is experts are considering in big data.
Method of storing and processing
Some of you may sometime have a question in your mind. How big data is stores and processed. You are going to get an answer to your question right here. The demand for big data velocity is high on the infrastructure of an organization. This can be used in mobile devices. The power of computing that is necessary to process huge volumes can easily make the single server overwhelmed. The same can be applied for the server cluster. The business houses must apply the suitable processing capacity to the big data task. This is done to achieve the required velocity. Here, hundreds and thousands of servers must be present to distribute the processing task at ease. The work of processing big data is done through advanced technologies like Apache Spark and Hadoop. Proper resource management is a vital phenomenon.
The challenge remains in getting the cost-effectiveness of the said velocity. There are many big corporate houses as well as the leaders who are ready to invest in the storage infrastructure of the big data. This is essential so that the workload can be handled efficiently. The sensory data within the organization are treated among the special issue. The storage infrastructure within the organization must be made in such a way that even the data that does not work 24/7 can be stored. The raw data can include the list. Cloud computing is also a factor that is considered over here. One of the methods through which hosting a big data system can be possible is through the public cloud computing system. It is quite important to note that a public cloud provider has the capacity for storing the data to the level of petabytes. It also does scaling up of a required number of data to complete the big data analytical project. The business over here is benefited as they only pay for the time of computing and storage. More facts are found at leading peer-reviewed journals.
List of public cloud providers
Most of you must have used the service of public cloud providers. This would need a cloud interface. But, you have never known the names associated with the same. Some of the popular names in this connection are:
- Microsoft Azure HDInsight
- Amazon EMR ( Elastic Map Reduce)
- Google Cloud Dataproc
Through the following ways the big data can be stored in the cloud environment:
- Cloud objects storage at a lower cost. This is none other than Amazon’s simple storage service
- Hadoop distributed file system ( HDFS)
- NoSQL database
- Relational database.
Challenges faced by big data
The article has stated several facts about the benefits and importance of big data. It is used in a large amount in several types of businesses starting from IT to the health sector. Yet, there are several challenges which one may face. It will include its processing capacity. It is hard for big data to design a big architectural project. It is very important to tailor and fit the big data according to the need of a specific organization. For example, the need for big data in a production business will not be similar to that of the business dealing with educational services. Very complex data becomes hard to manage.
The machine learning is going to be a positive point. The facts can also come out of the rational database. The experts from the field of computer science are very well aware of the challenges faced by big data. The team of application developers set the appropriate tool for the fulfillment of the required task. Most of the people miss an important fact, i.e. if any business deploys or proceed to manage big data system, special skill is important. Only the experts can deliver such skills. Now, if the business wishes to get such experts, the payment which they are likely to take will be too high as well. Under such circumstances, only the big corporate houses can avail of such benefits. The small traders suffer like always.
Conclusion
It is quite important to note that all the data types can be stored within the data lake. This is based on the big data with Hadoop. There is yet another name where it is stored. Yes, it is known as the cloud object storage. The big data application also comes with the offer of multiple data sources that are not at all integrated. To cite an example, the project with big data analytics will easily measure the panel in which project success is going to be mandatory. This will also measure the chances of future sales of such products. This can be done by the process of correlating between the sales data found out in the past along with the return data. This will be much more effective with the reviews available in the market posted by the online buyers.
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