Big Data Services

The Telecommunications Industry and Big Data Services

The telecommunications industry is a vast industry that deals with the global exchange of information over long distances through electronic means. The telecommunications market is diverse and often confronted with a range of technologies ranging from cell phone innovations to internet access innovations such as Skype, among others (Kaminskaite, 2016). There’s also the mobile money banking innovation, which has significantly dominated the telecommunications market. As a result, mobile companies continue to benefit in this market. However, one of the most important developments in this industry is the use of large data-driven services (Kaminskaite, 2016). The innovation helps various firms in collecting, managing as well as analyzing vast amounts of both structured and unstructured data. The multiple companies can increase their revenue through the establishment of new services such as marketing and sales, product development, improved customer services and retention. Globally, the use of significant data services in various institutions and firms is a very beneficial tool towards growth and development. It is a significant milestone in the telecommunications industry.

Globalization and its Impact on the Telecommunications Industry

Globalization is one of the driving forces for the continuous developments in the telecommunications industry. Nearly all organizations in the modern business rely on legacy data to monitor the progress of the companies (Fox & Shockley, 2013). In the past, business strategies were aimed at acquiring large numbers of new customers and were facilitated by the use of broad quantitative metrics. With time, markets have become competitive, and the needs for differentiation have made firms seek various innovations to remain in business. The operational business models have been transformed to explore a lasting relationship with customers. As such, the focus shifted from the desire to acquire new customers for most businesses to customer satisfaction and retention. Besides, meaningful data metrics are used to scale-up sales, marketing techniques as well as employee performance and operation processes (Fox & Shockley, 2013).

Challenges in the Development of Big Data Services and Possible Solutions

Data, whether personal or business is a vital asset in the modern world. It is almost impossible to underestimate the value of big data and analytics. Data is prone to grow every day as much as its importance hence; the need to protect it at all costs. It is essential to devise efficient measures on how to handle large volumes of data. Investing in Big Data Analytics is a sure way of securing the future growth of various firms and brands. Analytics seeks to gain insights crucial to business operations from big data. Thus, for a firm to successfully implement big data analytics, a vibrant investment in people, skills, and processes is essential. Also, companies should be ready to incorporate big data in their business operations due to the rapid growth in technology. Companies are often faced with the challenge of analyzing which technology best suits its daily activities. Besides, there is a significant talent gap for experts specializing in Big Data Analytics. As such, there are fewer human resources to handle the vast field. Therefore, there is a need for more experts in this area, if it is to emerge successful in the global perspective. Another major challenge in the development of Big Data is the overwhelming volumes of data available for data practitioners to handle every day. The practitioners have a hard task of making such data readily accessible to company directors and managers. As such, there is the need to incorporate the diversity of data into an analytical platform for efficiency (EDUCBA, 2016).

Methods of Implementing Big Data Services

Notably, organizations are striving to identify successfully, capture, manage and analyze data in attempts to develop useful decision-making insights. As such, they require the services of analytical experts and a clear understanding of data sciences and approaches. To implement Big Data services, machine learning and artificial intelligence such as intelligence applications can be incorporated to suit business operations. Also, an organization needs to purchase data analysis appliances and software that match their data volumes to be handled. This will enhance easy management and control of data for the various requirements. Besides, an organization needs to identify and create a data platform that best serves its needs (Yedavalli, 2017). It could be a platform based on tracking sales, keeping customer or employee records as well as the service offering. Also, data analysis experts have to consider data aspects such as ingestion, harmonization, analysis, visualization, and democratization when designing big data platforms for various companies. Secure stakeholders involvement in the implementation of Big Data is also essential. Therefore, organizations should have a well stipulated strategic plan for successful implementation of Big Data solutions.

Effects of Big Data Services

Big data presents numerous changes in how businesses are run and operated. It has dramatically revolutionized marketing and sales. Advanced big data algorithms, as well as advanced data analysis techniques, are making it possible for most businesses to attain optimal prices for various products. Also, technological advancements are opening up online markets for organizations through software and mobile applications. This encourages globalization as people can purchase commodities from all over the world. Besides, it is easy to shape routine pricing decisions in companies that produce fixed goods. In marketing strategies, big data is efficient in providing the right content for release to the market at each stage of the product sales cycle (Columbus, 2016). It also gives a direction on how to manage and maintain customer relations. However, investing in Big Data systems will slowly face out the workforce from various organizations. The use of big data in marketing and sales will render many people unemployed. As such the number of jobless individuals will rise. Also, the shift of organizations to using significant data services will result in a change of interest concerning education. Many people will desire to further their studies along with data analysis as a marketable career in the job markets. Besides, big data services have resulted in a plus in the telecommunications industry, hence greater profits for industry practitioners.

Conclusion

Therefore, organizations should embrace the use of Big Data services in their business operations. The innovation presents an excellent opportunity for business growth and development to firms of any nature. It is clear that businesses already using big data to manage their operations are far much better than their competitors. Big data reduces the amount of paperwork to be done, saves time thus a higher rate of productivity. Also, employees and customers will be more comfortable in an environment where their information is valued. As such, Big Data is an excellent opportunity for a firm to establish its strong client base through sales and marketing. Some organizations may risk exiting the market for reluctance to embrace advancements in technology.

References

Columbus, Louis. (2016). Ten Ways Big Data is Revolutionizing Marketing and Sales. Retrieved on 29 November, 2017 from www.forbes.com/sites/louiscolumbus/2016/05/09/ten-ways-big-data-is-revolutionizing-marketing-and-sales/#3272fe8121cf

EDUCBA. (2016). 5 Important Challenges and Solutions of Big Data Analytics. Retrieved on 28 November, 2017 from www.educba.com/5-challenges-of-big-data-analytics/

Fox, Bob. Shockley, Rebecca. (2013). Analytics: Real-world Use of Big Data in Telecommunications. Retrieved on 28 November, 2017 from www-935.ibm.com/services/multimedia/Anaytics.pdf

Kaminskaite, Julija. (2016). Top 10 Innovations in the Telecommunications Industry. Retrieved on 28 November, 2017 from www.giminstitute.org/top-10-innovations-in-telecommunications-industry/

Yedavalli, Nageswar. (2017). Best Practices for Implementing Big Data and Data Sciences for Analytics. Retrieved on 29 November, 2017 from www.aberdeenessentials.com/big-datapro-essentials/best-practices-implementing-big-data-data-sciences-analytics/