Computer Information System
Computer Information Systems
Information System代写 The most appropriate device and technologies for use by the company include IBM Bb2 and Oracle Database 12c but the most app.
Big Data Analytics
ABC Co. Ltd owns retail stores in California. The most appropriate device and technologies for use by the company include IBM Bb2 and Oracle Database 12c but the most app. These are the most preferred database systems because they offer client support and security. Also, the technologies are widely used and hence have a frequent update for bugs, safety, and functionalities. The IoT devices that the company require include retail website, mobile app, and servers. Information System代写**成品
Goals and Objectives Information System代写
The selected devices and technologies constitute a part of big data analytics. In business, big data providers and the ability to pursue new business models beside traditional ones. In technology it seeks to provide new techniques and complexities to derive value from the data. In technology, it brings economic advantages to the company. Big data analytics aim to get solution to modern organizational problems. The data is analyzed to generate new insights and intelligence about the market and target customers.
Company will use structured and unstructured data collected and stored in the database systems 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 essential in making projections on financial markets or political elections. Information System代写**成品
The database system selected will be deployed using servers through the company website and mobile applications. Both the apps and websites will be used to for customer services as well as gather data which will be stored in the databases for analytics. However, for optimum functioning of these devices and technologies, the company will be required to invest in securing them from risks and cyber threats. It can be done using firewalls and anti-viruses like Kaspersky and Cisco ASA 5500 Series.
Furthermore, the present computer systems and network will need to be upgraded to meet the new standards of data management and internet connections. The employees will also need to get training on new technologies use and security measures.
SWOT Analysis Information System代写
|IBM Bb2 and Oracle Database 12c
|Website, app, and servers
i. Client support and security
ii. Larger consumer data
iii. Implementation of data analytics
iv. Improved decision-making based on data collected
v. Better visualization of modern phenomena
i. Expensive to implement
ii. Need additional security technologies
i. Larger customer reach
ii. Company bargaining power
i. Vulnerable to insecurity
i. Artificial intelligence in data mining
ii. Business and organizational learning
iii. Development of better tools
i. Obsolescence of humans due to technologies like human-like machines
ii. Cyber threats and data security
iii. Data rapidly and hence may not be manageable in future
i. Integration of AI technologies
ii. Open to the global market
iii. Integration with internet firewalls
ii. Consumer privacy
Implementation and Integration Issues Information System代写
In 2016, Gartner reported that many organizations are unable to implement with big data initiatives at the piloting stage. The report found that more than 85 percent of organizations surveyed said that they could not effectively propel their significant data initiatives to production (Gartner, 2016). Therefore, organizations are impeded by substantial 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 has reported seven common challenges with big data as shown below. Information System代写**成品
a. Dealing with data growth
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, stacks of tablets can reach the 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 promptly
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 extensive data, organizations use ETL and analytics tools in the bid to reduce time for data analysis and reporting. Information System代写**成品
c. Recruiting and retaining big data talents
Big data requires experts whose demand has increased and hence their salaries are dramatically increasing. Therefore, the need for skills 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 shows 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 a variety of sources such as social media, emails, client feedback, etc. It is incredibly challenging 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 challenge of big data integration still exists. Information System代写**成品
e. Validating data
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 a 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). The new technologies and devices may not be compatible with current tools and software. The existing infrastructure is based on traditional configurations and securities which may present security loopholes to the databases, servers, and website. Information System代写**成品
g. Organizational resistance
A survey by NewVantage Partners shows 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 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, the company may fear its implementation and integration into the business. As such, the company will be required to create an open culture for changes.
Besides, the current systems need overhaul of replacement with better and modern technologies which will accommodate variations in the business model. The company also miss the necessary human resources for the implementation and integration of the techniques and devices to the business operations. Information System代写**成品
Therefore, the company needs to have open culture that is flexible enough to assume changes at any time even if is changing of roles and responsibilities. Data governance is mostly seen as a political move where processes and people are disturbed, and competencies and roles are awarded and withdrawn. The data governance will need acceptance and communication by the stakeholders who must have a good understanding of technical and business aspect of the data governance.
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 Information System代写
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