9.2.1 Data Generation Infrastructure Providers

Perhaps the first place to begin identifying the clusters is by noting a new group of companies that enable generation and collection of data that may be used for developing analytical insights. Although this group could include all the traditional points of sale systems, inventory management systems, and technology providers for every step in a company's supply/value chain and operations, we mainly consider new players where the primary focus has been on enabling an organization to develop new insights into its operations as opposed to running its core operations. Thus, this group includes companies creating the infrastructure for collecting data from different sources.

One of the emerging components of such infrastructure is the “sensor.” Sensors collect massive amount of data at a faster rate and have been adopted by various sectors such as health care, sports, and energy. For instance, some of the major players manufacturing sensors to collect health information are AliveCor, Apple, Google, Garmin, Shimmer, Jawbone, Kinsa, Netatmo, and Fitbit. Likewise, the sports industry is using sensors to collect data from the players and field to develop strategies to improve performance. Examples of the companies producing sports-related sensors include Sports Sensors, Zepp, Shockbox, and others. Similarly, sensors used for traffic management are produced by Advantech B+B SmartWorx, Garmin, Sensys Network, and many others.

Sensors play a major role in Internet of Things (IoT), and are an essential part of smart objects. Sensors comprising machine-to-machine communication are driving growth of IoT. The leading players in the infrastructure of IoT are Intel, Microsoft, Google, IBM, Cisco, General Electric, Smartbin, SIKO Products, Omega Engineering, Apple, and SAP. There are many industrial Internet of Things providers that develop industry-specific sensors, but those are too numerous to mention. This cluster is probably the most technical group in the ecosystem.

9.2.2 Data Management Infrastructure Providers

This group includes all of the major organizations that provide hardware and software targeting the basic foundation for all data management solutions. Obvious examples of these include all major hardware players that provide the infrastructure for database computing–IBM, Dell, HP, Oracle, and so on; storage solution providers such as EMC (recently bought by Dell) and NetApp; companies providing indigenous hardware and software platforms such as IBM, Oracle, and Teradata; data solution providers offering hardware and platform-independent database management systems such as SQL Server family of Microsoft; and specialized integrated software providers such as SAP fall under this group. This group also includes other organizations such as database appliance providers, service providers, integrators, developers, and so on that support each of these companies' ecosystems.

Several other companies are emerging as major players in a related space, thanks to the network infrastructure enabling cloud computing. Companies such as Amazon (Amazon Web Services), IBM (Bluemix), Microsoft (Azure), General Electric (Predix), and Salesforce.com pioneered to offer full data storage and analytics solutions through the cloud that now have been adopted by several companies listed above.

A recent crop of companies in the Big Data space are also part of this group. Companies such as Cloudera, Hortonworks, and many others do not necessarily offer their own hardware but provide infrastructure services and training to create the Big Data platform. This would include Hadoop clusters, MapReduce, NoSQL, Spark, Kafka, Tez, Flume, and other related technologies for analytics. Thus, they could also be grouped under industry consultants or trainers enabling the basic infrastructure. Full ecosystems of consultants, software integrators, training providers, and other value-added providers have evolved around many of the large players in data management infrastructure cluster. Some of the clusters below will identify these players because many of them are moving to analytics as the industry shifts its focus from efficient transaction processing to deriving analytical value from the data.

9.2.3 Data Warehouse Providers

Companies with a data warehousing focus provide technologies and services aimed toward integrating data from multiple sources, thus enabling organizations to derive and deliver value from their data assets. Many companies in this space include their own hardware to provide efficient data storage, retrieval, and processing. Companies such as IBM, Oracle, and Teradata are major players in this arena. Recent developments in this space include performing analytics on the data directly in memory.

Another major growth sector has been data warehousing in the cloud. Examples of such companies include Snowflake and Redshift. Major companies from other related sectors are also moving into this space–SAS and Tableau are good examples. Companies in this cluster clearly work with all the other sector players in providing data warehouse solutions and services within their ecosystem, and hence act as the backbone of analytics industry. It has been a major industry in its own right and, thus, a supplier and consumer of analytics talent.

9.2.4 Middleware Providers

Data warehousing began with a focus on bringing all the data stores into an enterprise-wide platform. Making sense of these data has become an industry in itself. The general goal of middleware industry is to provide easy-to-use tools for reporting or descriptive analytics, which forms a core part of BI or analytics employed at organizations. Examples of companies in this space include Microstrategy, Plum, and many others. A few of the major players that were independent middleware players have been acquired by companies in the first two groups. For example, Hyperion became a part of Oracle, SAP acquired Business Objects, and IBM acquired Cognos. This sector has been largely synonymous with the Business Intelligence providers offering dashboarding, reporting, visualization services to industry, building on top of the transaction processing data, and the database and data warehouse providers. Thus, many companies have moved into this space over the years, including general analytics software vendors such as SAS, or new visualization providers such as Tableau, or many niche application providers. A product directory at TDWI.org lists 201 vendors just in this category (http://www.tdwidirectory.com/category/business-intelligence-services) as of June 2016, so the sector has been robust. This sector is attempting to move toward the data science segment of the industry. On the other hand, software companies that have focused on visualization are incorporating capabilities that were once the domain of middleware in terms of customized reports and aggregate-to-detail analyses.

9.2.5 Data Service Providers

Much of the data an organization uses for analytics is generated internally through its operations, but there are many external data sources that play a major role in any organization's decision-making. Examples of such data sources include demographic data, weather, data collected by third parties that could inform an organization's decision-making, and so on. Several companies realized the opportunity to develop specialized data collection, aggregation, and distribution mechanisms. These companies typically focus on a specific industry sector and build upon their existing relationships in that industry through their niche platforms and services for data collection. For example, Nielsen provides data sources to their clients on customer retail purchase behavior. Another example is Experian, which includes data on each household in the United States. Omniture has developed technology to collect web clicks and share such data with their clients. Comscore is another major company in this space. Google compiles data for individual Web sites and makes a summary available through Google Analytics services. Other examples are Equifax, TransUnion, Acxiom, Merkle, Epsilon, and Avention. This can also include organizations such as ESRI.com, which provides location-oriented data to their customers. There are hundreds of other companies that are developing niche platforms and services to collect, aggregate, and share such data with their clients. As noted earlier, many industry-specific data aggregators and distributors exist, which are moving to offer their own analytics services. Thus, this sector also is a growing user and potential supplier of analytics talent, especially with specific niche expertise.

9.2.6 Analytics-Focused Software Developers

Companies in this category have developed analytics software to analyze data that have been collected in a data warehouse or are available through one of the platforms identified earlier (including Big Data). It can also include inventors and researchers in universities and other organizations that have developed machine learning algorithms for specific types of analytics applications. We identify major industry players in this space along the three types of analytics: descriptive, predictive, and prescriptive analytics.

9.2.7 Application Developers: Industry-Specific or General

The organizations in this group use their industry knowledge, analytical expertise, solutions available from the data infrastructure, data warehouse, middleware, data aggregators, and analytics software providers to develop custom solutions for a specific industry. Thus, this industry group makes it possible for the analytics technology to be used in a specific industry. Of course, such groups may also exist in specific user organizations. Most major analytics technology providers such as IBM, SAS, and Teradata clearly recognize the opportunity to connect to a specific industry or client and offer analytic consulting services. Companies that have traditionally provided application/data solutions to specific sectors are now developing industry-specific analytics offerings. For example, Cerner provides electronic medical records (EMR) solutions to medical providers and their offerings now include many analytics reports and visualizations. Similarly, IBM offers a fraud detection engine for the health insurance industry, and it is working with an insurance company to employ their Watson analytics platform in assisting medical providers and insurance companies with diagnosis and disease management. Another example of a vertical application provider is Sabre Technologies, which provides analytical solutions to the travel industry, including fare pricing for revenue optimization and dispatch planning.

This cluster also includes companies that have developed their own domain-specific analytics solutions and market them broadly to a client base. For example, Nike, IBM, and Sportvision develop applications in Sports Analytics to improve the play and increase the viewership. Acxiom has developed clusters for virtually all households in the United States based upon the data they collect about households from many different sources. Credit score and classification reporting companies (FICO, Experian, etc.) also belong in this group. This field represents an entrepreneurial opportunity to develop industry-specific applications. Many companies emerging in web/social media/location analytics are trying to profile users for better targeting of promotional campaigns in real time. Examples of such companies and their activities are as follows: YP.com employs location data for developing user/group profiles and targeting mobile advertisements, Towerdata profiles users on the basis of e-mail usage, Qualia aims to identify users through all device usage, and Simulmedia targets advertisements on TV on the basis of analysis of a user's TV-watching habits.

Growth of smartphones has spawned a complete industry focused on specific analytics applications for consumers as well as organizations. For example, smartphone apps such as Shazam, Soundhound, or Musixmatch are able to identify a song on the basis of first few notes and then let the user select it from their song base to play/download/purchase. Waze uses real-time traffic information shared by users, in addition to the location data, for improving navigation. Voice recognition tools such as Siri on iPhone, Google Now, and Amazon Alexa are leading to specialized applications for very specific purposes in analytics applied to images, videos, audio, and other data that can be captured through smartphones and/or connected sensors. Smartphones have also elevated the sharing economy providers. Recently, the sharing economy has gained an immense popularity for the transportation services and has given rise to companies such as Uber, Lyft, Curb, and Ola. The sharing economy concept has also been used by companies such as Airbnb, VRBO, and Couchsurfing for hospitality services. Many of these companies are exemplars of analytics leading to new business opportunities.

Online social media is another hot area in this cluster. Undoubtedly, Facebook is the leading player in the space of online social networking followed by Twitter and LinkedIn. Moreover, the public access to their data has given rise to multiple other companies that analyze their data. For example, Unmetric analyzes the Twitter data and provides solutions to their clients. Similarly, there are several other companies that focus on social network analysis.

Other satellites around this planet are the group of industries in specific industries. To illustrate a few, consider finance, legal, life sciences, and security sector. Companies such as Affirm, Lending Club, Payoff, OnDeck, ZestFinance, Cignify, Wonga, and Dataminr provide financial services to their clients. Several companies are providing legal services to their clients using data analytics. Some of these companies are Brightleaf, Counselytics, Everlaw, Judicata, Premonition.ai, DiligenceEngine, eBrevia, Lex Machina (now acquired by LexisNexis), and Ravel. The group of industries producing life sciences applications include 3scan, 23andMe, Deep Genomics, HumanDX, Kyruus, HealthTap, Metabiota, uBiome, Vital Labs, Ovuline, Tute Genomics, Zephyr Health, Zymergen, and many others. Due to the increasing cases related to cyber security, several companies have emerged in this area. Companies creating security applications for their clients are Area 1 Security, CounterTack, Cybereason, Cylance, Feedzai, Fortscale, Guardian Analytics, Keybase, Recorded Future, Sift Science, Signifyd, ThreatMetrix, and so on. New companies keep coming up, which focus on applications targeted at a specific industry. Turck (2017) provides names of many additional industry-focused analytics providers.

A trending area in the application development industry is the Internet of Things. Several companies are building applications to make smart objects. For example, SmartBin has made Intelligent Remote Monitoring Systems for the waste and recycling sectors. Several other organizations are working on building smart meters, smart grids, smart cities, connected cars, smart home, smart supply chain, connected health, smart retail, and other smart objects.

One of the emerging trends in the analytics industry is deep learning. It involves use of hierarchical algorithms to model higher level abstractions in the data. The industry players in this group include Google, with their products named Tensorflow, Apache Singa, Microsoft Cognitive Toolkit, and several other open-source packages such as MXNet, Theano, and OpenNN. Another evolving label in the analytics industry is virtual reality (VR) analytics. Companies such as Google, Facebook, and GE are investing and showing great interest in this emerging area.

The start-up activity in this sector is growing and is in major transition due to technology/venture funding and security/privacy issues. Nevertheless, the application developer sector is perhaps the biggest growth industry within analytics at this point. This cluster provides an innovative pool of talent to the hiring managers.

We next introduce the “inner orbit” of the analytics planetary system. These clusters can be called analytics accelerators. Although they may not be involved in developing the technology directly, these organizations have played a key role in shaping the industry.

9.2.8 Analytics Industry Analysts and Influencers

This cluster includes three types of organizations or professionals. The first group is the set of professional organizations that provide advice to the analytics industry providers and users. Their services include marketing analyses, coverage of new developments, evaluation of specific technologies and development of training/white papers and so on. Examples of such players include organizations such as the Gartner Group, The Data Warehousing Institute, Forrester, McKinsey, and many of the general and technical publications and Web sites that cover the analytics industry. Gartner Group's Magic Quadrants are highly influential and are based on industry surveys. Similarly, TDWI.org professionals provide excellent industry overview and are very aware of current and future trends of this industry.

The second group includes professional societies or organizations that also provide some of the same services but are membership based and organized. For example, INFORMS is focused on promoting analytics. Special Interest Group on Decision Support and Analytics (SIGDSA), a subgroup of the Association for Information Systems, also focuses on analytics. Most of the major vendors (e.g., Teradata and SAS) also have their own membership-based user groups. These entities promote the use of analytics and enable sharing of the lessons learned through their publications and conferences. They may also provide recruiting services and are thus good sources for locating talent.

A third group of analytics industry analysts is what we call analytics ambassadors, influencers, or evangelists. These folks have presented their enthusiasm for analytics through their seminars, books, and other publications. Illustrative examples include Steve Baker, Tom Davenport, Charles Duhigg, Wayne Eckerson, Bill Franks, Malcolm Gladwell, Claudia Imhoff, Bill Inman, and many others. Again, the list is not inclusive. All of these ambassadors have written books (some of them bestsellers!) and/or given many presentations to promote the analytics applications. Perhaps another group of evangelists to include here is the authors of textbooks on business intelligence/analytics who aim to assist the next cluster to produce professionals for the analytics industry.

9.2.9 Academic Institutions and Certification Agencies

In any knowledge-intensive industry such as analytics, the fundamental strength comes from having students who are interested in the technology and choose that industry as their profession. Universities play a key role in making this possible. This cluster, then, represents the academic programs that prepare professionals for the industry. It includes various components of business schools such as information systems, marketing, management sciences, and so on. It also extends far beyond business schools to include computer science, statistics, mathematics, and industrial engineering departments. Universities are offering undergraduate and graduate programs in analytics in all of these disciplines, though they may be labeled differently. A major growth frontier has been certificate programs in analytics to enable current professionals to retrain and retool themselves for analytics careers. Certificate programs enable practicing analysts to gain basic proficiency in specific software by taking a few critical courses of schools offering. INFORMS Web site includes a list of many such programs, with new ones being added daily.

Another group of players assists with developing competency in analytics. These are certification programs to award a certificate of expertise in specific software. Virtually every major technology provider (IBM, Microsoft, Microstrategy, Oracle, SAS, Tableau, and Teradata) has its own certification program. These certificates ensure that potential new hires have a certain level of tool skills. On the other hand, INFORMS offers a Certified Analytics Professional (CAP) certificate program that is aimed at testing an individual's general analytics competency. Any of these certifications give a college student additional marketable skills.

The growth of academic programs in analytics is staggering. Only time will tell if this cluster is overbuilding the capacity that can be consumed by the other clusters, but at this point the demand appears to outstrip the supply of qualified analytics graduates and this is the most obvious place to find at least entry level analytics hires.

9.2.10 Regulators and Policy Makers

The players in this component are responsible for defining rules and regulations for protecting employees, customers, and shareholders of the analytics organizations. The collection and sharing of the users' data require strict laws for securing privacy. Several organizations in this space regulate the data transfer and protect users' rights. For example, the Federal Communications Commission (FCC) regulates interstate and international communications. Similarly, the Federal Trade Commission (FTC) is responsible for preventing data-related unfair business practices. The International Telecommunication Union (ITU) regulates the access to Information and Communication Technologies (ICT) to underserved communities worldwide. On the other hand, a nonregulatory federal agency named the National Institute of Standards and Technology (NIST) helps advance the technology infrastructure. There are several other organizations across the globe that regulate the data security. This is a very important component in the ecosystem so that no one can misuse the consumers' information.

For anyone developing or using analytics application, it is crucial to have someone on the team who is aware of the regulatory framework. These agencies and professionals who work with them clearly offer unique analytics talents and skills.

9.2.11 Analytics User Organizations

Clearly, this is the economic engine of the whole analytics industry, and therefore, we represent this cluster as the core of the analytics planetary system. If there were no users, there would be no analytics industry. Organizations in every industry, regardless of size, shape, and location, are using analytics or exploring the use of analytics in their operations. These include private sector, government, education, military, and so on around the world. Companies are exploring opportunities in analytics space to try to gain/retain a competitive advantage. Specific companies are not identified in this section. The goal here is to see what type of roles analytics professionals can play within a user organization.

Of course, the top leadership of an organization, especially in the information technology group (Chief Information Officer, etc.), is critically important in applying analytics to its operations. Reportedly, Forrest Mars of the Mars Chocolate Empire said that all management boiled down to applying mathematics to a company's operations and economics. Although not enough senior managers subscribe to this view, the awareness of applying analytics within an organization is growing everywhere. A health insurance company executive once told us that his boss (the CEO) viewed the company as an IT-enabled organization that collected money from insured members and distributed it to the providers. Thus, efficiency in this process was the premium they could earn over a competitor. This led the company to develop several analytics applications to reduce fraud and overpayment to providers, promote wellness among those insured so they would use the providers less often, generate more efficiency in processing, and thus be more profitable.

Virtually all major organizations in every industry that we are aware of are hiring analytical professionals under various titles. Figure 9.2 is a word cloud of the selected titles of our program graduates at Oklahoma State University from 2013 to 2016. It clearly shows that analytics is a popular title in the organizations hiring graduates of such programs. Other key words appear to include terms such as Risk, Health, Security, Revenue, Marketing, and so on.

Of course, user organizations include career paths for analytics professionals moving into management positions. These titles include project managers, senior managers, and directors, all the way up to Chief Information Officer or Chief Executive Officer. This suggests that user organizations exist as a key cluster in the analytics ecosystem, and thus can be a good source of talent. It is perhaps the first place to find analytics professionals within the vertical industry segment.

Other than the talent sources discussed in this chapter, the analytics talent can be found within the organization itself. It is possible that the current employees of the organization have the common analytical skills, which are not visible. Such employees can be identified by hosting analytics competitions in the organization. In addition, the individuals with Lean Six Sigma certifications can be of interest to the analytics industry.