Database Assignment

Database Assignment
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Abstract
The paper mainly focuses on database tools such as data stores and software challenges associated with big data. However, the article begins by acknowledging big data as a valuable opportunity for individuals and organizations because it facilitates the decision-making process by providing tertiary information. The essay goes a step further by identifying and breaking down variety, volume, and growth rate (velocity) as the primary characteristic of big data that offer challenges to database tools. As the paper explains, the difficulties experienced as a result of these characteristics include but not limited to security issues, storage space, data integration, and its validation. Considering these issues, it becomes hard for the users to optimally carry out their task efficiently because it requires more time and resources to analyze, secure, and store such vast information. Perhaps some of the most important issue regarding this data is its accuracy and usability because data may get interrupted due to security weaknesses of these tools.
Big data is a synonym term being for the large volume of data which organizations gather on a daily basis from various sources such as social networks. Big data analysis offers a range of benefits to organizations as well as individuals. For example, analysis of such data gives someone a leading insight for making informed decisions as well establishing optimal business strategic moves.

However, it is worth noting that big data has a negative side too. To begin with, it’s attributes of volume, velocity, and varieties are the key reasons why organizations have continually experienced some database tools challenges. It is a fact that data volume continues to increase in size in a double standard every year. Therefore, it requires a huge storage space which puts organizations to the task of scaling their data repositories and software frequently. Further complicating the situation is the variety of formats which big data represents (Kaisler, Espinosa & Money, 2013).
Most of the gathered data happen to be unstructured which has placed a limitation on database tools capability to store as well as analyze the same. Therefore, a significant challenge entails the capacity of hardware and software tools to deal with high data growth. Perhaps one thing that is exonerating the issue is the fact that photos and audio formats require considerable storage space and a lot of time to analyze due to their unstructured form. Another challenge experienced in using database tools by users involves data integration. Such limitations emanate from the nature of big data comprising of a variety of different formats and types. More so, the fact that such data come from different places such as social media, email systems, and enterprise applications makes it rich in varieties (Cooper & Anne, 2009). As a result, working with such data becomes a hard thing to integrate and reconcile the same especially when creating queries and reports. Today, a considerable number of enterprises still consider that technological advancement needs to focus on developing tools which can handle data integration more efficiently.
Data validation is another universal limitation capability that characterizes database tools. The issue of data governance arises with the increase in the volume of data especially with the fact that some of the information comes from different sources. The reality is that organizations get information from a range of systems whose data fails always to agree (Kaisler, Espinosa & Money, 2013). Therefore, considering such a scenario, making such records to agree with each other for purposes of usability and accuracy happens to be a demanding task. To combat such challenge, it requires a review of policies and advancement of technology, else, it involves a group of data analysts to ensure that big data stores are accurate all the time. Lastly, providing the security of the big data is also a challenge and a big concern too. It takes additional security measures to secure data repositories against attacks from malicious people such as hackers. Tools for storing such vast data in most cases possess numerous weak points through which one can gain unauthorized access. Therefore, it requires the deployment of complementary security measures to limit and control access to these data stores. Some of the most used complementary mechanisms include data encryption, segregation, and access control among others (Cooper & Anne, 2009).
References
Cooper, J., & James, A. (2009). Challenges for database management in the internet of things. IETE Technical Review, 26(5), 320-329.
Kaisler, S., Armour, F., Espinosa, J. A., & Money, W. (2013, January). Big data: Issues and challenges moving forward. In System sciences (HICSS), 2013 46th Hawaii international conference on (pp. 995-1004). IEEE.