The potential for using big data and analytics is endless -- and growing.
We've only tapped into the tip of iceberg of what we can do with big data and analytics. Organizations of the future will need to be more data driven by applying insights to everything from key business processes to fundamental operations. Instead of using intuition to make decisions, organizations will infuse analytics into everything that clients, partners or employees touch. These could range from management systems, to machine-to-machine processes or daily decisions and tasks.
Companies should also consider using the best data -- generated outside of an organization -- in conjunction with data that already resides within the enterprise and pair up the information with increased use of social media and mobile devices. Security, privacy and governance will be a requirement for big data implementations.
I'm often asked: "Is it better to outsource data development or keep it in-house?"
The most important factor for an individual organization in answering that question is the anticipated longevity of the program. Organizations cannot be short-sighted and focus only on the here and now. They need a technology infrastructure that will support all types of data from an ever increasing array of sources, and deliver analytics and insights at scale, ensuring their business’ growth and success. There is a danger of trying to create the entire platform in house due to the perception of "open source" and "it is all Java."
Another argument that is often heard for keeping it in house is "we know our data and domain better." While both statements are true, data curation and development is a very complex undertaking, especially when dealing with multiple data sources. A number of such "curators" are emerging who do this for specific domains and source data sets like social media, financial reports, SEC filings, clinical trial data and retail data.
The Open Data movement is spawning more such data sets, which have a guarantee of consistent curation and governance, of both public and proprietary data from multiple cloud providers. In order to take advantage of such readily available data in combination with enterprise sources of record, an organization may need a strategy of a hybrid model that leverages on-premise infrastructure and the cloud. Such a hybrid model also helps manage costs of implementation and continued maintenance.
Or, "What are the attributes of the best big data platforms?"
Big data platforms started as a collection of machines that provided integrated compute and storage with built-in resiliency for hardware, network and software failures. They satisfied the 4 "V's:" volume, variety, velocity, and veracity. Organizations should develop big data platforms that have the ability to perform rapid and accurate analytics, and that can take advantage of and enhance existing open technologies. Building a big data platform in the cloud will enable a company to scale, while optimizing resources. There are easy-to-use tools and platforms that exist now, which can help organizations make sense of the new data-driven norm.
Organizations need to think strategically, have foresight and plan ahead. The strategy should consider not only how to start a big data and analytics approach to doing business, but also how to sustain it.
Here are four tips on how organizations could get started:
- Define the challenge and understand the opportunity that big data and analytics can present for an organization. Establish the organization's goal -- whether it is cost savings, increased ROI, or reduced risk when implementing a big data program.
For example, Millesima Winery is one of the world's largest wine merchants based in Bordeaux, France. The wine merchant's goal was to expand its business globally while continuing to offer individualized shopping experiences. A cloud-based solution enabled Millesima to quickly set up online stores in several regions. By using big data and analytics to identify site visitors by where they live and their purchase histories, Millesima can now offer personalized service that caters to visitors' tastes. Other companies can draw from Millesima Winery's experience as they expand globally.
- Choose the data that needs to be analyzed and where it is located. Depending on the industry, different types of data are more critical to an organization than others. These various types of data need to be located and analyzed in order to obtain critical insights. It is best to conduct the analytics where the data resides, because that approach is faster and more cost effective than stuffing all the data inside a data warehouse. At the same time, choose the right technology tailored for an individual organization.
- Evolve the organization's culture to recognize that big data is not only an Information Technology (IT) issue, but also the responsibility or the entire organization. By starting with the C-suite, an organization can apply big data and analytics to growth opportunities. Executive leaders will want to see the larger implications that increased use of big data and analytics could present for an organization. Map out potential savings and the increased ROI that will impact the bottom line and future growth of the business.
- Consider creating the position of Chief Data Officer in the C-suite so there's a heightened focus on harnessing the power of big data and analytics and ensure that the right team and skills are in place. Having people with the right skills is equally as important as having the right technology. At the same time, build a data scientist role or data science team. According to Gartner, there are more than 100 Chief Data Officers serving large enterprises today, which is double the number of CDOs in 2012. We believe the role will continue to emerge as a vital member of the C-suite.
As a data scientist, I realize that there's a need for people skilled in working with data and analytics, and the role will continue to evolve to help shape industries and drive successful business outcomes. But the reality is that all employees of a business will need to understand data, whether they work in marketing and sales and want to create compelling customer experiences, or in the HR departments and need to develop more precise ways to recruit, cultivate, develop and retain their top performers. Big data is developing curiosity-driven and evidence-based cultures and workforces and will continue to do so at an even more rapid rate.
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