Our project took us on an exploration of Watson IBM Analytics and their competitors. The basis of our comparison involves the concepts of cloud computing and business intelligence tools. The top Analytics and Business Intelligence software players and top three market share percentages are SAP, SAS, IBM, Oracle, Microsoft, Qlik, Tableau, Teradata, MicroStrategy, and Informatica (Markovski, 2016). In this analysis, we will focus on SAP HANA Analytics, SAS Visual Analytics, and Google BigQuery. These services can all be considered cloud-based analytics platforms with varying features. Similar to IBM Watson Analytics, several processes have to happen in order to identify, combine and manage multiple sources of data, and build advanced analytic capability into business processes for better decision-making. The processes include database management, download, storage, and ad hoc queries.
COST
Cloud computing has brought about different services, SaaS, PaaS and IaaS, that have helped cut maintenance costs up to 80 % from IT budgets (Gallaugher, 2016).
SAP HANA is a PaaS on which customers must subscribe first before adding on applications. SAP Hana can be deployed on premise, in the cloud, or hybrid. SAP HANA offers 3 options HANA AWS, HANA Base, and and HANA platform cloud. HANA platform cloud seems to offer the best features for analytics and build-on applications. For analytics, clients must add the SAP BusinessObjects at additional subscription fee. With 150 employees, SAP Hana Cloud, User-based package will be the package that fit the organization size, starting with the most basic one at $25/user/month and going up to $126/user/month. However, the price structure is complex, and depends on the size of memory used on top of an additional subscription to the Businessobjects- Analytics. SAP HANA platform cloud costs vary based on the size as well: from $ 539 (32GB), $ 647 (64GB) up through $90, 000 per month (Paunova, 2015). The subscription based license usually include maintenance and upgrade services, and supports 100 standard and 300 premium users. HANA Cloud platform option includes hardware and licensing on demand. There is no requirement for any maintenance or support. The license package comes with HANA cloud platform where solutions can be built. There are apps which are available as well as ability to develop apps yourself; performance and reliability. Some of the limitations are that SAP HANA cloud platform cannot be used in conjunction with other application servers and is not suitable to be used as database which accommodates regular data loads (paunova,2015).
Google BigQuery offers flexibility and low cost pricing, encryption and security of data as well as integration with third party developers. BigQuery separates the concepts of storage and compute and allows you to scale and pay for each independently.Features include data management, queries in SQL, integration and access control. Flexible pricing options such as capping the daily costs to an amount selected are optional. Costs can be a pay-as-you-go model or a flat-rate monthly price for those who need cost predictability. BigQuery charges for data storage, streaming inserts, and for querying data, but loading and exporting data are free of charge.(Google cloud platform).
SAS The Cloud/ Saas version, SAS Visual Analytics is $6,000 USD per unit (SAS, 2016). Another source shows pricing for SAS Visual Analytics Saas as $1365/ month for 61GB memory, 150GB storage; $3395/ month for 122GB, 300GB storage; and $6695/ month for 244GB, 600 GB storage (Amsio, n.d.).
VALUE
SAP HANA Business Objects
As a PaaS, SAP HANA can dramatically reduce costs, by some degree to outsourcing jobs associated with acquiring, running and maintaining information systems. Value is created by cost savings, scalability, high quality of specialized services and the flexibility SAP HANA provides for customizing based on customers needs. The cost savings can range from 25 to 60%. The platform includes the hardware, operating system, development tools, testing and hosting and data is stored in live memory, instead of data having to first be downloaded from a data warehouse (Hickins, 2013). SAP HANA has similar features to Watson analytics: natural language, predictive analytics, and one click analysis, as do many of its competitors.
Google BigQuery
The value in Google BigQuery is the flexibility and full integration it offers with other Google and 3rd party products and services. However, the training curve is a little steeper than IBM Watson, because it does not use natural language or one-click analysis. BigQuery can ingest data at 100K rows per second and can be downloaded from Google cloud storage or datastores, allowing for global availability, transparent data replication and full integration. In addition to SQL queries, you can read and write data in BigQuery via Cloud Dataflow, Spark and Hadoop. BigQuery users can plug into other google products (Google Analytics premium, Data Studio and Cloud Storage) and partner with 3rd party developers (Looker, Tableau, Qlik, Talend, Google Analytics, SnapLogic etc.) to fully integrate and synthesize a complete system to easily load, process data, query and make interactive visualizations of the data.
SAS Visual Analytics
SAS Visual Analytics provides a complete platform for analytics visualization, revealing insights and relationships in data and an easy-to-use, self-service interface. This system is very good at analyzing and displaying interactive visualizations of the data. Some key features include: descriptive, predictive and prescriptive analytics, out-of-the-box accessibility, and One-click ability to create time-period based calculations. Data can be easily queried from a seamless group of viewing modes. Forecasts can be generated instantly with forecasting confidence intervals added (SAS Institute Inc., 2015, p. 4). Similar to Watson Analytics, scenario analysis can see how a forecast will shift with changes in variables. SAS Visual Analytics can be deployed on-site on a single server or in a distributed environment. It can also be utilized in a private cloud or public cloud such as AWS, or through a subscription to SAS Visual Analytics for SAS Cloud.
RISK
One of the major risks of all three systems are those associated with services provided over the internet on cloud based platforms. These include dependence on host for connectivity and flexibility, security issues dealing with remote access and preventing infiltration and legal issues with data storage. In regards to risk prevention and awareness for all systems, IBM’s ‘Security Intelligence’ website reports that identifying vulnerabilities is a good start, but detailed remediation recommendations are important to help harden (SAP HANA) all databases and subsequently lock down the system from future exploits of known vulnerabilities (Paliwal, 2015).
SAS Visual Analytics
SAS Visual Analytics provides a complete platform for analytics visualization, revealing insights and relationships in data and an easy-to-use, self-service interface. This system is very good at analyzing and displaying interactive visualizations of the data. Some key features include: descriptive, predictive and prescriptive analytics, out-of-the-box accessibility, and One-click ability to create time-period based calculations. Data can be easily queried from a seamless group of viewing modes. Forecasts can be generated instantly with forecasting confidence intervals added (SAS Institute Inc., 2015, p. 4). Similar to Watson Analytics, scenario analysis can see how a forecast will shift with changes in variables. SAS Visual Analytics can be deployed on-site on a single server or in a distributed environment. It can also be utilized in a private cloud or public cloud such as AWS, or through a subscription to SAS Visual Analytics for SAS Cloud.
RISK
One of the major risks of all three systems are those associated with services provided over the internet on cloud based platforms. These include dependence on host for connectivity and flexibility, security issues dealing with remote access and preventing infiltration and legal issues with data storage. In regards to risk prevention and awareness for all systems, IBM’s ‘Security Intelligence’ website reports that identifying vulnerabilities is a good start, but detailed remediation recommendations are important to help harden (SAP HANA) all databases and subsequently lock down the system from future exploits of known vulnerabilities (Paliwal, 2015).
SAP HANA
SAP HANA Cloud Platform advertises as a reliable and secure cloud application and offers their own robust security services to help people connect securely with technology (SAP, 2016), but security seems to be a weak area for them. High risks for customers come from exploited vulnerabilities, and could result in significant business loss to customers running SAP HANA in applications. Other consequences related to an exploit or data breach include failed compliance, brand reputation impact and declining customer trust resulting in churn (Paliwal, 2015). Most importantly, Pensiamo’s use of IBM Watson analytics requires high security due to HIPPA laws, and restricted access to medical records.
BigQuery
BigQuery automatically encrypts and replicates your data to ensure security, availability and durability. There is additional protection of data with strong role-based ACLs that the user configures and controls using Google Cloud Identity & Access Management system. Full control over who has access to the data stored in Google BigQuery is available and recommended. Identity access is controlled through ACLs, either on the project or on the individual datasets you want to manage (2014).
SAS Visual Analytics
SAS Visual Analytics provides IT with effective ways to defend and manage data integrity and security. Similar to the security measures available for Watson Analytics, SAS safeguards security via setting privacy levels. That is, some data is classified and access is restricted so that it can only be viewed by certain groups. According to Williams (2015) from the SAS Institute, SAS has implemented security measures in Visual Analytics, including row-level security, which specifies who can access particular rows in a SAS LASR Analytic Server. Permissions to access data can be set at group level or user level. There is an SAS Metadata Server in which group identities can be created. For data building, users must belong to a SAS Visual Analytics Users group, a Visual Data Builder Administrators group, or both.
The figure below summaries overall features, cost, value, and risk in score ranging from 1 5; 5 being good and fairly priced, and 1 being High and expensive.
BigQuery
BigQuery automatically encrypts and replicates your data to ensure security, availability and durability. There is additional protection of data with strong role-based ACLs that the user configures and controls using Google Cloud Identity & Access Management system. Full control over who has access to the data stored in Google BigQuery is available and recommended. Identity access is controlled through ACLs, either on the project or on the individual datasets you want to manage (2014).
SAS Visual Analytics
SAS Visual Analytics provides IT with effective ways to defend and manage data integrity and security. Similar to the security measures available for Watson Analytics, SAS safeguards security via setting privacy levels. That is, some data is classified and access is restricted so that it can only be viewed by certain groups. According to Williams (2015) from the SAS Institute, SAS has implemented security measures in Visual Analytics, including row-level security, which specifies who can access particular rows in a SAS LASR Analytic Server. Permissions to access data can be set at group level or user level. There is an SAS Metadata Server in which group identities can be created. For data building, users must belong to a SAS Visual Analytics Users group, a Visual Data Builder Administrators group, or both.
The figure below summaries overall features, cost, value, and risk in score ranging from 1 5; 5 being good and fairly priced, and 1 being High and expensive.
Figure 6.1
SCORE out of 5
5 Excellent
1 unacceptable
|
IBM WATSON
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SAP HANA
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GOOGLE BIGQUERY
|
SAS VISUAL ANALYTICS
|
FEATURES
|
5 EXCELLENT
|
5 EXCELLENT
|
3 MEDIUM
|
5 EXCELLENT
|
COST
|
4 LOW $
|
3 MED $$
|
5 LOW $
|
1 HIGH $$$$$
|
VALUE
|
4 GOOD
|
4 GOOD
|
3 MED
|
4 GOOD
|
RISK
|
5 LOW
|
1 HIGH
|
5 LOW
|
3 MED
|
TOTAL
|
18
|
13
|
16
|
13
|
Features, cost, and risk were components of differentiation. Value was very good (4) across the board due to the cost savings and low switching costs for all 4 cloud based platforms. The systems that had natural language, one-click predictive analysis, and was easy to use had a high score of 5 in features. BigQuery uses SQL and therefore was weighted in the medium range (3) for features. The high cost of SAS Visual Analytics and the high risk factor of SAP HANA eliminated these two platforms from further consideration. BigQuery is not necessarily competitive with Watson analytics because the research did not provide us with sufficient evidence of machine learning capability and predictive analysis. Our team recommends IBM Watson analytics for Pensiamo and management of its health supply chain because of its excellent features, all-in-one analytics package with flexibility and integration capability, low cost and company support.
REFERENCES
Amsio. (n.d.) Saas now pricelist: SAS Visual Analytics. Retrieved from https://www.sas.com/content/dam/SAS/bp_de/doc/other2/pricelist-sas-visual-analytics-in-der-cloud-saas-now.pdf
Dinsmore, T.W. (2015, April 30). How to buy SAS as Visual Analytics. Retrieved from https://thomaswdinsmore.com/2015/04/30/how-to-buy-sas-visual-analytics/
Gallaugher, J. (2016). Chapter 14.Information systems: A manager's guide to harnessing technology. Retrieved from http://catalog.flatworldknowledge.com/bookhub/reader/28393?cid=253359
Google. (n.d). Google Cloud Platform retrieved from https://cloud.google.com/bigquery/
Hickins, M. (2013). SAP Details HANA Pricing. Retrieved from http://blogs.wsj.com/cio/2013/04/12/sap-details-hana-pricing/
Markovski, M. (2016). Top 10 Analytics and BI Software Vendors and Market Forecast 2015-2020. Retrieved from https://www.appsruntheworld.com/top-10-analytics-and-bi-software-vendors-and-market-forecast-2015-2020
Paunova, M. (2015). Which SAP HANA licensing option is right for my organisation? Retrieved from https://www.linkedin.com/pulse/which-sap-hana-licensing-option-right-my-organisation-milena-paunova
Sheldon M. (Dec 12 2014). Industry blog, stack overflow. Retrieved from http://stackoverflow.com/questions/27432641/service-account-limiting-access-to-only-big-query
SAP BusinessObjects Cloud: All Analytics. All Users. One Product. (2016). Retrieved from http://go.sap.com/documents/2015/10/3cf98911-497c-0010-82c7-eda71af511fa.html
https://hcp.sap.com/capabilities/security/secure-development.html#
SAS Institute Inc. (2015). SAS Visual Analytics Fact Sheet. Retrieved from
https://www.sas.com/content/dam/SAS/en_us/doc/factsheet/sas-visual-analytics-105682.pdf
SAS. (2016). SAS Visual Analytics for SAS Cloud. Retrieved from https://www.sas.com/store/products-solutions/sas-visual-analytics-for-sas-cloud/prodVANLYTSCW.html?storeCode=SAS_US and https://hcp.sap.com/capabilities/security/secure-development.html#
Paliwal, V. (2015, Jun 15). Uncovering Risk From SAP HANA Vulnerabilities Can Be Simple and Easy. Retrieved from https://securityintelligence.com/uncovering-risk-from-sap-hana-vulnerabilities-can-be-simple-and-easy/
Williams, Z. (2015). Row-level security and SAS Visual Analytics. SAS Institute Inc., Cary, NC. Retrieved from https://support.sas.com/resources/papers/proceedings15/SAS1779-2015.pdf
Zencos. (2015, March 23). SAS VA administration: What’s in an SAS VA role.
https://www.zencos.com/blog/sas-va-administration-whats-in-a-role/
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