Computer Information System代写 Big Data Analytics代写

Computer Information System

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Computer Information Systems

Computer Information System代写 Computer Information Systems：Data is valuable in the world today. The value of any data is measured through analytics.

Big Data Analytics

Data is valuable in the world today. The value of any data is measured through analytics. Big data has been growing since the inception of internet and other technologies. To date, the importance of big data cannot be underestimated given the benefits that have so far associated to its analytics. Thus, as big data continue to expand and grow, the importance of big data analytics will continue to grow in everyday for both personal and business applications. Essentially, the size of big data is growing in size and volume each day and hence it is critical to evaluate the manner in which big data analytics is addressed in everyday life.

Goals and Objectives Computer Information System代写

Big data analytics has may purposes and goals which can be summarized as business, technology and finance goals. In business big data provides and ability to pursue new business models beside traditional ones. In technology it seeks to provide new techniques and complexities in order to derive value from the data. In technology, it brings economic advantages to companies that have adopted such solutions. Big data analytics seek to get solution to modern organizational problems using data. The data is analyzed to generate new insights and intelligence about the market and target customers. Computer Information System代写**成品

Companies use structured and unstructured data to build models for analyzing buying behaviors, consumer opinions on the products and analysis of competitors.

The goal is to harness the available methods of acquiring prospective customers through effective marketing such as campaigns, advertising and offers etc. Also, giving data is used in politics that provide information on trends of consumer thoughts and behaviors that help in marketing research for new products. The data is important in making projections on financial markets or political elections.

Moreover, governments, government agencies and public services providers take keen interest in big data analysis. Computer Information System代写

They use the data in intelligence monitoring of contents in social networks and other websites to protect the nation from threats. Similarly, the policing services use the big data to t carry out website monitoring of contents in the bid to fight crimes.

Furthermore, the public sectors use the dig data other than controlling illegal activities.

They sectors use data not only from web but also from ministries, public services managers in transport, energy, corporations and other state agencies like ISTAT and CENSIS found in Italy. The large data is used to the performance of government functions and other entities for optimum public service deliver and hence avoid inefficiencies and wastage.

SWOT Analysis Computer Information System代写

1.Strengths

Large data

Solution to modern issues

Better visualization of modern phenomena

2.Weaknesses

Expensive to mine and store

Unstructured

Not secure

Need specialized tools

3.Opportunities Computer Information System代写

Artificial intelligence

Business and organizational learning

Development of better tools

4.Threats

Obsolescence of humans due to technologies like human-like machines

Cyber threats and data security

Growing rapidly and hence may not be manageable in future

Implementation and Integration Issues Computer Information System代写

A study conducted by NewVantage Partners Big Data Executive Survey 2017 established that in the Fortune 1000 business leaders surveyed 95 percent of them undertake big data analytics in their operations (2017). Unfortunately, only less than 50 percent of these companies have tangible results from big data initiatives.

In 2016, Gartner reported that many organizations are unable to implement with big data initiatives at piloting stage. The report found that, more than 85 percent of organizations surveyed said that they could not effectively propel their big data initiatives to production (Gartner, 2016). Computer Information System代写**成品

Therefore, it is clear that organizations are impeded by major challenges when implementing and integrating big data strategies. This argument is confirmed by IDG Enterprise 2016 Data & Analytics Research (2016) when it was found that more than 90 percent of organizations faced underpinning issues with big data initiatives. Various research conducted have reported seven common challenges with big data as shown below.

a. Dealing with data growth Computer Information System代写

A report by IDC on Digital Universe estimates that data stored in information systems are doubling every two years. These data will be enormous to the extent that by 2020 stack of tablets can reach moon over six times (2014). Unfortunately, organizations have responsibility or liability to more than 85 percent of these data. The data is also not only large but also unstructured and hence difficult to search and analyze. IDG report (2016) found that managing unstructured data that comes with big data is a challenge which has rose “from 31 percent in 2015 to 45 percent in 2016.”

b. Generating insights in a timely manner

A report by PwC on Global Data and Analytics Survey 2016 found that found, “Everyone wants decision-making to be faster, especially in banking, insurance, and healthcare” (2016). Due to large data, organizations use ETL and analytics tools in the bid to reduce time for data analysis and reporting.

c. Recruiting and retaining big data talents Computer Information System代写

Big data requires experts whose demand has increased and hence their salaries are dramatically increasing. Therefore, the demand for talents is high and so is the cost of recruitment and retaining them. The argument is confirmed by 2017 Robert Half Technology Salary Guide report that show that big data scientists are highly paid ranging between $135,000 and $196,000 (2017).

d. Integrating disparate data sources

Big data has issues of integration due to variety of sources such as social media, emails, client feedbacks etc. It is incredibly difficult to combine and reconcile data from different sources for good report. Although vendors have offered to solve the problem through data integration tools, many organizations feel the problem of big data integration still exist.

e. Validating data Computer Information System代写

Organizations similar data from different sources but the data do not always agree. According to AtScale 2016 Big Data Maturity Survey, data governance is the main areas of concern. Therefore, organizations invest heavily on getting these records agree to maintain accuracy, usability and security.

f. Securing big data

Big data stores are target of hacking and advanced persistence threats. A survey by IDG established that 39 percent use additional security measures in their big data databases (2016).

g. Organizational resistance

A survey by NewVantage Partners show that 85.5 percent of respondents’ organizations are committed to big data initiatives (2016). However, out of these 85.5 percent, only 37 percent are successful in implementing and integrating data-driven culture in the organization. The main impediments included lack of organizational alignment, poor management adoption and understanding and resistance which took 4.6 percent, 41 percent, and 41 percent respectively.

People, Process and Governance Issues Computer Information System代写

Big data governance involves people and processes as well as technologies use in the management and protection of the organization’s data assets. Despite many advantages of data governance, organizations fear its implementation and integration into the business. Below are the hurdles that most organizations face in the implementation of data governance.

Data governance requires open culture that is flexible enough to assume changes at any time even if is changing of roles and responsibilities. Because of this, data governance is mostly seen as a political move where processes and people are disturbed and competencies and roles are awarded and withdrawn. Secondly, data governance needs acceptance and communication by the stakeholders who must have a good understanding of technical and business aspect of the data governance. Computer Information System代写**成品

Another issue is convincing the stakeholders on the need for data governance so that they can approve the needed budget. Therefore, the processes are hindered by the deficiency in the information processing and invisible resource needs of such programs.

References

AtScale. (2016). 2016 Big Data maturity survey. Retrieved from https://www.atscale.com/resource/2016-hadoop-maturity-survey-results

Gartner. (2016). Gartner survey reveals investment in big data is up but fewer organizations plan to invest. Retrieved from https://www.gartner.com/en/newsroom/press-releases/2016-10-04-gartner-survey-reveals-investment-in-big-data-is-up-but-fewer-organizations-plan-to-invest

IDG. (2016). 2016 Data & Analytics Research. Retrieved from https://www.idg.com/tools-for-marketers/tech-2016-data-analytics-research/

IDC. (2014). The digital universe of opportunities: rich data and the increasing value of the internet of things. Retrieved from https://www.emc.com/leadership/digital-universe/2014iview/index.htm

NewVantage Partners. (2017). Big Data executive survey 2017 (pp. 1-16). New York: NewVantage Partners LLC. Retrieved from http://newvantage.com/wp-content/uploads/2017/01/Big-Data-Executive-Survey-2017-Executive-Summary.pdf

PwC. (2016). PwC’s Global Data and Analytics Survey 2016. Retrieved from https://www.pwc.com/us/en/services/consulting/analytics/big-decision-survey.html

Robert Half. (2017). 2019 Technology & IT Salary Guide. Retrieved from https://www.roberthalf.com/salary-guide/technology

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