In many cases, a single product cannot provide all of these capabilities. Most of the available products and services do not simply output the information that an enterprise needs. Often, therefore, vendors form partnerships to offer their products as a combined solution. For example, Cisco and IBM have a partnership through which they provide their big data Analytics technology as a merged offering. But there are some vendors offering simpler turnkey analytics solutions. For example, Google's BigQuery is a cloud-based managed service.
The Future of Analytics
A Large, Fast Growing Market
The market for big data analytics, which is already very large, is expected to grow quickly. It will reach an annual $203 billion by 2020, according to IDC, up from $130 billion in 2016.7 IDC expects banking particularly to drive growth in the field, along with government users, manufacturers, and professional services firms.
Also, businesses that engage in big data analytics are a hot target for venture capital investments.8
Changes to Some Core Business Practices
The advent of big data analytics has the potential to dramatically change core practices in many fields. One primary example is in a "smart city," which is the urban use of advanced technologies to perform a variety of municipal services. This is an enormously large market. One study estimated that by 2020, $758 billion will be spent annually on such programs.9 Describing how big data analytics are used in a smart city program in Oulu, Finland, Susanna Pirttikangas discussed its applications for traffic management: "In order to avoid traffic congestion, decrease emissions, and increase safety on the roads, you need information about traffic speeds, construction, weather, and even available parking spaces. You also need information about other drivers, bus locations, vehicles, vehicles behind corners, and so on."10 The amount of data is critical. "With enough data, you can make reliable assumptions about the situation, and in traffic, where situations emerge fast, you need the information to be updated and delivered quickly."
Legal and Regulatory Obstacles
There are some legal and regulatory issues that could impede the growth of big data analytics. For example, there is a push to use analytics in responding to disasters. But as noted by the National Security Telecommunications Advisory Committee (NSTAC), many of the types of data sharing that would be critical in an emergency are not today allowed in normal circumstances.11 NSTAC is therefore seeking legal and regulatory modifications that would permit such data exchanges in certain situations. The rules are only one obstacle, however. The NSTAC also points out that the technology framework and standards to facilitate shared data analytics are not fully in place.
Applications in Key Sectors
Recently, big data has been put to wider, more critical use in several key market segments. These uses are just beginning to fully emerge, but they are showing the direction that the marketplace and technology may take in the coming years. Examples of emerging applications include the following:
- Sharing data among treatment centers battling opioid use12
- Investigating crimes and make tactical policing decisions13
- Improving the delivery and profitability of healthcare services14
Recommendations for Implementation
According to a study of the goals that Fortune 1000 companies have for using big data, the following were most important:
- Decrease expenses
- Find new avenues for innovation
- Launch new products/services
- Increase revenue
- Increase the speed of current efforts
- Transform business for the future
- Establish a data driven future15
Executives are a crucial part of planning to implement big data analytics in order to achieve these goals. Before key decisions about technology can be made, organizations must first set their analytics strategy. In doing so, the following questions will be crucial:
- What decisions need to be made?
- What data helps us to make decisions?
- In what form is data best provided to us?
- Where, when, and to whom does data need to be delivered?
Using big data analytics effectively will take a change in mindsets and even processes and job roles, however. Organizations cannot simply approach the new analytic capabilities in the same way that they have traditionally used information. Studying how organizations in a variety of industries are using the technology can provide ideas for adapting to this new way of approaching analytics.16
References
1 Andrew McAfee and Erik Brynjolfsson. "Big Data: The Management Revolution." Harvard Business Review. October 2012.
2 Thomas H. Davenport and Jill Dyché. "Big Data in Big Companies." SAS Institute. May 2013.
3 Lisa Morgan. "12 Barriers to Real-Time Analytics." InformationWeek. July 12, 2016.
4 Lisa Morgan. "8 Smart Ways to Use Prescriptive Analytics." InformationWeek. June 28, 2016.
5 Jonathan Vanian. "Has Big Data Gone Mainstream?" Fortune. January 13, 2016.
6 Andy Patrizio. "Big Data Companies." Datamation. June 14, 2017.
7 Scott Ferguson. "Big Data, Analytics Market to Hit $203 Billion in 2020." InformationWeek. October 4, 2016.
8 Tom Sullivan. "Big Data Analytics, Telemedicine, Wearables Rank High among $1.4B Worth of Health IT Investments in 2016." Healthcare IT News. April 13, 2016.
9 "Smart Cities Market Worth 757.74 Billion USD by 2020." MarketsandMarkets. May 2016.
10 Susanna Pirttikangas. "Analyzing Data in the Internet of Things." Proceedings of Strata + Hadoop World 2015. O'Reilly. 2016.
11 Chose Gunter. "Big Data and Disasters." Federal Computer Week. May 11, 2016.
12 Jennifer Bresnick. "For Opioids and Substance Abuse, Big Data Analytics Is Just the Beginning." HealthIT Analytics. 2017.
13 Andrew Guthrie Ferguson. "The Rise of Big Data Policing." TechCrunch. October 22, 2017.
14 Jennifer Bresnick. "70% of Healthcare Execs Pin Growth to Big Data Analytics Skills." HealthIT Analytics. October 16, 2017.
15 Randy Bean. "How Companies Say They’re Using Big Data." Harvard Business Review. April 28, 2017.
16 For example, see McKinsey & Company. "How Companies Are Using Big Data and Analytics." McKinsey & Company. April 2016.
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