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Glimpses of the Future: Big Data in 2018

How software outsourcing, CDOs, and data mining will drive big data growth.

Big data's robust growth is on course to continue into 2018 and beyond, in fact, according to Statista, the big data market will nearly double in size to US$65.2bn by 2021. During the same period, global IP traffic is expected to grow 229% from its current volume of 121,694TB a month. The fast growth in big data has created a fertile seedbed for businesses to create new products that are designed to handle large volumes of data and make sense of colossal datasets. Software outsourcing companies are quickly developing products to provide big data storage, processing, and analytics to business clients. To meet the growing challenges of big data management, a new c-level role has emerged: Chief Data Officer (CDO). The CDO is responsible for managing big data and everything that pertains to it. In this article, we will talk about the big data trends to watch for 2018, the rise of the CDO, and how your business will benefit from finding the right combination of big data products and services for your business.

Big data and software outsourcing

Businesses realize that they cannot keep up with their own data needs from within their own organizations. As the demand for big data services grows, software outsourcing service providers are innovating ways to meet those needs. We may even see something in the form of Big Data Analytics as a Service (BDAaaS) or as a platform (BDAaaP). This kind of approach could provide a means through which analysts, marketers, and sales staff can interact with the data, creating custom visualizations and reports without a degree in data science.

[Did you know PSL Corp was selected as a Clutch Global Leader in IT Outsourcing Services?]

The rise of the Chief Data Officer

Big data is a mission-critical part of most business operations. And, its growing importance is driving the need for a Chief Data Officer (CDO) to manage a company's data. The core roles and responsibilities of a CDO include:

  • Recognizing the big picture data strategy and priorities
  • Asking the right questions of the data
  • Maximizing the value of data sets through innovation
  • Aligning the goals of business units and IT to data-driven business goals
  • Ensuring regulatory compliance and business governance

The successful CDO must possess significant technical knowledge of data and data strategies in order to do the job well. As businesses recognize the value and importance of their data, we can expect to see a lot more businesses seeking to fill a CDO position.

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Big data security

Cyber threats, corporate espionage, and privacy present ongoing challenges. Businesses often lack the internal resources to safely store their data, so they look for a cloud-based solution. As businesses quickly outgrow their internal capacity to store and secure their own data, we can expect to see more businesses outsourcing big data storage to companies that have the capacity and robust security in place to protect that data. Don't assume, however, that security is a given. When you decide to outsource big data storage, make sure the provider will also keep your data as safe as possible.

To find the right outsource partner to store and secure your data, find a provider that knows the procedures and regulations of your industry. Find out how they comply with security rules and regulations. Find out from past clients how a provider you're considering stored and protected their data. And finally, when you choose a provider, make sure they sign off on legal agreements that ensure your data will be protected and have contingency plans in place to deal with any incidents that may occur.

Data mining

This is a part of big data analytics that isn't talked about much, yet is of fundamental importance to the analysis of huge data sets. Data mining was developed to dig through massive amounts of data, identify relevant patterns, and extract important information from those patterns. For example, basket analysis allows a business to see which items customers buy together. This helps retailers identify purchasing patterns that can be used to offer related products to customers and boost sales. Another type of data mining is sales forecasting, which is used to predict the time at which a customer will buy a product again. Data mining is a flexible technology that can be configured to produce results that are tailored to the unique needs of each business. Keep your eye out for a sharp uptick in demand for this service in 2018.

Looking ahead with big data

Big data will continue to make inroads as businesses find new ways to harness it. The current barriers to wider adoption will persist, largely due to a shortage of data specialists equipped with the skills required to effectively work with data. Outsource companies will develop services to meet growing big data needs and package them in ways that businesses will likely find attractive. Finally, CDOs will continue to advance ways to increase the value of their data sets through data-driven business goals, placing even greater importance on big data in 2018.

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Saturday, 16 December 2017

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