by Jelani Harper
There are three key questions that the Big Data market must answer in 2014 to justify its extensive hype, the latest of which includes a projection in Forbes that the marketplace will exceed $16 billion next year, growing faster than the entire IT market combined:
What is the most viable option for analytics?
What applications can specifically increase business value?
How can Big Data personalize the customer experience?
The simple answers to these questions revolve around the emerging trends of soliciting third-party vendors for analytics within the Cloud, applying Big Data for marketing purposes, and reducing the complexity of such data into discernible, accessible chunks of what has come to be known as “small data.”
The more complex answers incorporate various aspects of utilizing the Internet of Things’ role as a driver for Big Data, accounting for the shortage of knowledgeable Data Scientists, and asserting the continuing relevance of SQL.
Up in the Cloud
A Gartner report states that “Big Data technologies supplement – but do not replace – existing information management and analytics. As a result, Cloud adoption, with its supplementary nature, is the overriding technology that companies are using to derive value from Big Data.” Several factors contribute to the trend that third-party, Cloud-based service providers will likely become the go-to source for Big Data analytics in the near future:
Shortage of qualified Data Scientists: Despite the fact that there are growing numbers of formal educational institutions offering programs in Data Science, at present there is still a dearth of qualified personnel to fulfill these roles at organizations attempting to implement Big Data. This reality contributes to the fact that those who do have such qualifications can find ready employment at Cloud providers, which in turn can handle the needs of a multitude of organizations more readily than the paucity of Data Scientists can fulfill the employment needs of each organization attempting a Big Data initiative.
Explosion of the SOA market: There is a niche for Service Oriented Architecture for virtually all facets of the enterprise, including Analytics-as-a-Service and Cloud-based Business Intelligence. The ability to compile different data sets from anywhere in the world and readily access them makes Cloud options extremely cost-efficient and relevant. Forbes revealed that “cloud infrastructure will be the fastest-growing sub-segment of the big data market, with a 2013-2017 CAGR of close to 50%.”
Impact of the Internet of Things (IoT): The IoT has the potential to complicate Big Data analytics due to its increasing growth and the fact that much of its data generated is in real time and pertains to highly mutable factors (such as geo-location). Common analytics functions like predictive analytics, may be exacerbated by data from IoT. It is much more convenient to utilize the hardware and software expertise of service providers than to purchase, maintain, and analyze one’s own tools for this still rapidly evolving contributor to Big Data.
Business Applications
The adoption rates for Big Data are still relatively low for a variety of reasons including questions about governance issues, concerns for privacy, analytics and, perhaps most eminently, confusion about how to derive business value from this phenomenon. More progressive organizations are utilizing Big Data for transactional purpose which, although valuable, is still a far cry from unlocking Big Data’s full potential. Even Gartner predicts that “through 2017, 90% of the information assets from big data analytic efforts will be siloed and unleverageable across multiple business processes”.
Organizations can get ahead of this trend by tapping into the emerging market of enterprise Big Data applications, which are any variety of business applications supervised by a combination of business and IT personnel. Business objectives will determine relevant applications, which can include personalizing products to the creation of new services and products.
Personalize the Customer Experience
The capacity to revolutionize the data-driven marketing process is one of Big Data’s most tantalizing wins. Organizations across all industries can get ahead of the competition by utilizing Big Data for detailed target marketing by pitching products and services that specifically apply to the consumer’s interests. The abundance of sentiment data available online, for instance, can be processed to substantially alter customer interaction.
In addition to utilizing detailed information to personalize an organization’s marketing efforts to the customer, particularly savvy organizations will use Big Data to affect the way that consumers interact with them by offering consumer intelligence and options for which customers can access and manipulate their own accounts and data. The ability to utilize Big Data as a means to substantially change the everyday applications of data for both organizations and consumers is part of the growing phenomenon referred to as
Small Data: From Big to Little
Although small data can refer to data gleaned from conventional structured sources, small data also includes Big Data in its propensity for deriving insight and daily usage of data for any variety of operations, business, and consumer processes. A more succinct definition denotes that: “small data connects people with timely, meaningful insights (derived from big data and/or “local” sources), organized and packaged – often visually – to be accessible, understandable, and actionable for everyday tasks.”
Although the term may very well be the latest in a never ending series of catchphrases (such as smart data) for the expeditiously prudent application of data, the concept behind small data is valid and a testament to the direction that Big Data is heading towards in 2014. Cloud-based analytics can expedite the process of deriving insight from Big Data sets, which can be applied to specific business processes. Results can include knowing what products and services are working best and why, which inevitably leads to the development of new ones.
In such a way the customer experience becomes more personalized, as what began as Big Data is neatly compartmentalized into the most useful applications for organizations and consumers alike. Regardless of the term, this process of going from voluminous to specific represents Big Data’s full potential, which competitive organizations will act on in 2014.
SQL Triumphs
Although there is no shortage of options of accessing and querying Big Data through NoSQL platforms, there is no denying the comfort and familiarity of querying Big Data with SQL. SQL-based methods for utilizing Big Data will continue to emerge in 2014 and make substantial advances by becoming increasingly incorporated into Big Data platforms. A good indicator of this trend is the fact that Hadoop has become significantly more NoSQL friendly. Other telltale signs include the fact that vendors have begun equipping SQL tools to query JSON documents. NoSQL is definitely here to stay, but so is SQL.
More Than Hype
Big Data should finally move beyond its hype into a greater realization for organizations in a variety of industries in 2014. By focusing on specific business applications that provide demonstrable value to the enterprise, organizations that embrace the aforementioned trends should gain a significant advantage over competitors.
In hindsight, however, it is essential to note that the point of commonality existing between all of these trends is the emergence of third-party vendors providing Big Data insights to customers. Choosing such options may summon the usual questions of trust and security that have traditionally abounded regarding going outside the enterprise for data, but when compared to the costs saved, technical know-how gained and level of expedience at which such relevant data is garnered – as well as all of the tangible applications it can yield – this industry will likely take off.
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