process automation

Four Big Data Trends to Watch in 2014

2013 was arguably a banner year for Big Data, but the reality was that, beneath the hype, many organizations struggled to understand the value of Big Data. Now that 2014 is underway, more organizations are learning how to realize the potential of Big Data. Whether you are an early adopter or well down the Big Data path, watch for these four trends to gauge the pulse of Big Data this year.

4. Organizations will need Big Data training to achieve success. Organizations that master a broad-based, enterprise-wide approach to Big Data education will be more successful than those with a narrow IT focus.  As Big Data becomes a line item in IT budgets, and more organizations implement Big Data solutions, people with the knowledge and skills to execute and manage these solutions will be in high demand.

To bridge the talent gap, organizations will need to educate and up-skill their current IT professionals to be able to work with Big Data. However, to be successful, organizations will also need to educate decision makers and senior leaders to gain the Big Data acumen necessary to effectively achieve business results. This requires not only knowledge and insights into Big Data tools and technologies, but also a keen awareness of best practices, potential pitfalls, and relevant, industry-focused use cases.

3. Big-Data-as-a-Service will become more prevalent. Big Data implementations managed in-house might be possible for organizations that have adequate infrastructure and trained Big Data scientists and engineers; however, many organizations will need to take advantage of the growing number of Big-Data-as-a-Service (BDaaS) solutions.

BDaaS typically combines data storage (frequently secure cloud storage) with the power of Big Data Analytics applications as a managed third-party service. These solutions lessen the burden and cost of storing the data and running the application on organizational resources. With BDaaS, even organizations with limited Big Data knowledge will be able to reap the benefits of analyzing large datasets for actionable insights.

2. Novel forms of data, including data generated by machines, will lead to breakthroughs.  Applying advanced data analytics to the traditional data used in existing business and intelligence and data warehousing will have limited value.

Truly embracing new sources of Big Data, including public and third-party providers as well as data generated by machines (devices, sensors, and meters), and combining them with existing, proprietary data will provide a much richer landscape for advanced analytics to harvest.

1. Big Data initiatives will need enterprise-wide buy-in and collaboration. In many cases, Big Data projects within an organization have been siloed to the IT department, and even to specific infrastructure teams.

However, to fully realize the benefits of Big Data will require the collaboration of possibly unrelated business units. For example, the Service organization may derive value from Big Data insights on customer behavior, allowing the Sales organization to build more comprehensive customer profiles and deliver more targeted messaging.  Similar collaborations between different functions/business units can lead to a greater understanding of the benefits of Big Data across the organization.

With these and other developments on the horizon, 2014 promises to be the biggest year for big data yet.

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