3. Obstacles in Big Data Implementations

Heterogeneity and timeliness, security, incompleteness and scalability of the data are the biggest obstacles in analyzing big data.

Skilled people are required for the shift to Big Data. It requires people in the area of system analysis, domain knowledge, data analytics, database management and software developers. Large number of open source technologies available in the market for Big Data.

At every step of extraction and analysis the big data creates many challenges. In order to achieve success, we need to overcome many obstacles in the Big Data & Analytics process. First time the obstacles are encountered they take an wide quantity of time to be solved.

Many are trying to recognize the benefits of big data, while more than 1/5th of the respondents are still trying to gain knowledge more about big data. There are significant reliant of data management professionals trying to understand the basics, although the industry has written innumerable blogs and articles, white papers about big data.

Cost implications is one of the vital practical challenges faced by big data. Even though its been a decade since the implementation of Big Data analytics has started, the cost allegation of storing vast amount of data is still a subject of concern.

1. Data Collection:

The companies not only have to find and examine the appropriate data they need they must also find it quickly due to todays hypercompetitive business environment. The most important problem in the data collection step is heterogeneity of the data sources. Collecting the data from multiple sources is the first step of general big data schema. Challenges arise when the data sources are complex and sophisticated. The main source of data for Big Data stream is rapidly shifting from manual data entries to the data collected from sensors, social networks.

2. Integration:

The data that has been transferred must be stored in some form. Every day we create so much data that it costs companies fortune to store it in order for them to improve their business. The demand for storing the big data has increased so immensely and in such a fast pace.

The increasing amount of data and a need to analyze the given data in a timely manner for multiple purposes has created a serious barrier in the big data analysis process.

Storing such a huge sized data requires enormous amount of energy and resources. One of the problems of the Big Data is to find the best located servers to store the data. The server locations must also be energy efficient and scalable. The location is important due to the speed of transfer of the stored data to do the analyses.

3. Analysis:

The problems that data analysts face when dealing with an average size of data set emerge in more severe form for the big data. Most business decisions need to be made in a punctual manner. The companies that cannot modify their behavior to the changes in the market behavior in a timely manner have serious problems and will likely face severe problems in the future.

False and transitory correlation will most likely result in wrong decisions that can damage the company in the long term.

There are many huge analytical challenges that come along with big data.

Large number of advance skills are required to perform every type of analysis on enormous quantity of data. That can be unstructured, semi structured or structured.

4. Privacy and security:

The most important test in big data comprises responsive, conceptual, technical and also legal importance.

The personal records of any individual when combined with exterior huge number of data sets, it leads to the interpretation of latest facts about that individual. There can also be possibility that these kinds of details about the individual are private. This individual may not want the data owner or any other individual to know about that individual.

In order to add importance to the business of the organization, information concerning the individuals is collected and used. This is prepared by creating perceptions in their lives which they are ignorant of.

Big data predictive analysis advantages will be utilized by a well-educated person. On the further side underprivileged will be effortlessly recognized and treated inferior. In the future, this would be another very important arising outcome.