Business Intelligence Software
R is the most versatile language, with more thousand third party libraries almost for anything from Economics, Financial, and Scientific.
From Robert A. Muenchen, R for SAS and SPSS Users,
Why Learn R?
R has many benefits:
- R offers a vast array of analytical methods. There are several thousand
addon packages available for R on the Internet, and you can easily download
and install them within R itself.
- R offers new methods sooner. Since people who develop new analytic methods
often program in R, you often get access to them years before the
methods are added to SAS or SPSS.
- Many analytic packages can run R programs. These include: SAS, SPSS,
Excel, JMP, Oracle Data Mining, Statistica, StatExact, and others. This
provides you the option of using R functions without having to learn its
entire language. You can do all your data management in your preferred
software, and call the R functions you need from within it.
- R is rapidly becoming a universal language for data analysis. Books and
journals frequently use R for their examples because they know everyone
can run them. As a result, understanding R is important for your continuing
education. It also allows you to communicate your analytic ideas with a wide
range of colleagues.
- R’s graphics are extremely flexible and are of publication quality. They are
flexible enough to overlay data from different data sets, even at different
levels of aggregation. You are even free to completely replace R’s graphics
subsystem, as people have already done.
- R is very flexible in the type of data it can analyze. While SAS and SPSS
require you to store your data in rectangular data sets, R offers a rich
variety of data structures that are much more flexible. You can perform
analyses that include variables from different data structures easily without
having to merge them.
- R has object oriented abilities. This provides many advantages including
an ability to “do the right thing.” For example, when using a categorical
variable as a predictor in a linear regression analysis, it will automatically
take the proper statistical approach. If you like to develop your own analytic
methods, you’ll find much to like
in the power of R’s language. The vast array of add-ons for R demonstrates
that people who like to develop new methods like working in R.
- R’s procedures, called functions, are open for you to see and modify. This
makes it easier to understand what it is doing. Copying an existing function
and then modifying it is a common way to begin writing your own function.
Functions that you write in R are automatically on an equal footing with
those that come with the software. The ability to write your own completely
integrated procedures in SAS or SPSS requires using a different
language such as C or Python and, in the case of SAS, a developer’s kit.
- R has comprehensive matrix algebra capabilities similar to those in MATLAB.
It even offers a MATLAB emulation package
- R runs on almost any computer, including Windows, Macintosh, Linux,
- R is free. This has an obvious appeal to corporate users. Even academics
who purchase software at substantial discounts for teaching and internal
use will appreciate the fact that they can consult with outside organizations
without having to purchase a commercial license.
Is R Accurate?
When people first learn of R, one of their first questions is, “Can a package
written by volunteers be as accurate as one written by a large corporation?”
Just as with SAS and SPSS, the development of the main R package, referred
to as Base R plus Recommended Packages, is handled with great care. This
includes levels of beta testing and running validation suites to ensure accurate
answers. When you install R, you can ask it to install the Test Files,
which includes the tools package and a set of validation programs. See the R
Installation and Administration Manual  on the R help menu for details.
R’s Base and Recommended Packages currently consist of
the following packages: base, boot, class, cluster, codetools, datasets,
foreign, graphics, grDevices, grid, KernSmooth, lattice, MASS, methods,
mgcv, nlme, nnet, rpart, spatial, splines, stats, stats4, survival, tcltk,
tools and utils. Those packages, and the functions they contain, are roughly
When you buy software from SAS or SPSS, you can call or e-mail for tech
support that is quick, polite, and accurate. Their knowledgeable consultants
have helped me out of many a jam.
If you use the free version of R, you do not get a number to call, but you
do get direct access to the people who wrote the program and others who
know it well via e-mail. They usually answer your question in less than an
hour. Since they are scattered around the world, that support is around the
The main difference is that the SAS or SPSS consultants will typically
provide a single solution that they consider best, while the R-help list responders
will often provide several ways to solve your problem. You learn more
that way, but the solutions can vary quite a bit in level of difficulty.
There are companies that provide various types of support for a fee. Examples
of such organizations are Revolution Analytics, Inc., RStudio, Inc.,
and XL-Solutions Corporation.
SAS (From SAS for Dummies by Stephen McDaniel and Chris Hemedinger)
Isn’t SAS Just for Gurus?
You might assume that you need to be a statistician or math guru to use SAS,
but happily that’s not the case. In the last few years, SAS has made a significant
investment in making the unparalleled analytical and data management
capabilities developed over 30-plus years available to almost anyone with a
problem to solve in business, science, or government. With recent products
such as SAS Enterprise Guide and the SAS Add-In for Microsoft Office, SAS
has never been more accessible or flexible. These products provide userfriendly
interfaces and wizards to maximize the heavy-duty capabilities that
SAS has long provided to gurus!
Where SPSS Works from SPSS for Dummies by Arthur Griffith
More than one version of IBM SPSS Statistics 18 exists, for execution under
different operating systems.
IBM SPSS Statistics 18 for Windows can be run on Windows XP (32-bit) or on
Windows Vista (32-bit or 64-bit). You can run IBM SPSS Statistics 18 for Mac
on Macintosh 10.5x (Leopard) or on Macintosh 10.6x (Snow Leopard), both
32- and 64-bit. IBM SPSS Statistics 18 for Linux has been tested only on Red
Hat Enterprise Linux 5 and Debian 4.0, but it should run on any sufficiently
updated Linux system.
Qlik is a market leader in data discovery. It sells two products, both based on an inmemory associative
search engine. QlikView is a mature, selfcontained, tightly integrated development platform used by IT or
more technical users for building intuitive and interactive dashboard applications faster and easier than
traditional BI platforms. Qlik Sense is a new platform (released during September 2014) that gives
business users the ability to build their own dashboards while giving IT the ability to govern, manage,
scale and embed them.
Tableau’s intuitive, visualbased data discovery capabilities have transformed business users’ expectations
about what they can discover in data and share without extensive skills or training with a BI platform.
Tableau’s revenue growth during the past few years has very rapidly passed through the $100 million,
$200 million and $300 million revenue thresholds at an extraordinary rate compared with other software
and technology companies.
Tableau has a strong position on the Ability to Execute axis of the Leaders quadrant, because of the
company’s successful “land and expand” strategy that has driven much of its growth momentum. Many
of Gartner’s BI and analytics clients are seeing Tableau usage expand in their organizations and have had
to adapt their strategy. They have had to adjust to incorporate the requirements that new users/usage of
Tableau bring into the existing deployment and information governance models and information
infrastructures. Despite its exceptional growth, which can cause growing pains, Tableau has continued to
deliver stellar customer experience and business value. We expect that Tableau will continue to rapidly
expand its partner network and to improve international presence during the coming years.
Most of the lecturers in University of Sydney loves Filemaker. Though it was intended to retire all Filemaker
applications within five years. It drags on as it is very popular. It got excellent user interface, reports, advanced
scripting language and plug-ins that can be developed in C. It can integrate all in one.
The FileMaker Platform is a suite of tools used to easily build flexible database solutions for rapid deployment on
Windows and Mac, and to extend them to the web. The product line consists of FileMaker Pro, FileMaker Pro Advanced,
FileMaker Server, and FileMaker Server Advanced. FileMaker Pro is an encapsulated development and deployment
platform – no additional tools are needed to build and deploy applications. However many developers opt to use
FileMaker Pro Advanced in order to take advantage of the added customization and development tools included
in the software. If a FileMaker application needs to be securely shared, FileMaker Server is added to manage the
databases. Or FileMaker Server Advanced can be used to host even larger groups of databases, provide ODBC/JDBC
connectivity and share databases over the web with more users than FileMaker Pro alone. The FileMaker Platform is
ideal for: • Solutions that are currently based on spreadsheets or paper • Retrieving and exchanging data with enterprise
systems • Data tracking, report generation, and analysis • Workflow solutions for the department or workgroup The
FileMaker Platform is designed to help the non-programmer (subject matter expert) become more productive in collecting,
processing, and analyzing information. The award-winning FileMaker Pro provides the tools to build a customized user
interface with a relational database and business logic in a Supercharging Return on Investment with Rapid Application
Development Tools 4 single unified Windows and Mac application. Incorporating these three elements into one product
has proven to be very effective and places a lighter cognitive load on the knowledge worker or other users. (Supercharging
Return on Investment with Rapid Application Development Tools)
Undoubtly MS SQL has good ground in Database Management with its sister software and support available. When it
comes to managing your data, the choice is clear: Microsoft is an industry leader in ODBMS. Don’t take our word for it;
read Gartner’s assessment of the ODBMS landscape and see how Microsoft stacks up.
Gartner recognised Microsoft as a Leader once again in the 2015 Magic Quadrant for Operational Database Management
Systems, positioning it furthest to the right on the axis for completeness of vision, and closest to the top on the axis for ability to execute.
Gartner view on MS SQL,
- Market vision: Microsoft’s market-leading vision consists of NoSQL (Azure DocumentDB and Azure Tables), cloud offerings
(including hybrid cloud), the use of analytics in transactions (HTAP) and support for mobility. Its vision for in-memory
computing across products, hybrid cloud implementations and a “cloud first” strategy is ahead of its competitors.
- Strong execution: Microsoft SQL Server is an enterprisewide, mission-critical DBMS capable of competing with products f
rom the other large DBMS vendors. Gartner’s 2014 market share data shows Microsoft as the No. 2 vendor in terms of total DBMS revenue.
- Performance and support: Reference customers were very positive, with the performance of SQL Server, documentation,
support, ease of installation, integration and operation all rated highly.
- Market image: Although SQL Server is an enterprise-class DBMS, Microsoft continues to struggle to dispel a perception
of weakness in this area. Inquiries from Gartner clients demonstrate a continuing perception that SQL Server is not used
for mission-critical enterprisewide applications — a view that inhibits wider use of SQL Server as a primary, enterprise-class DBMS.
- Lack of an appliance: Microsoft still lacks an appliance for transactions (one comparable to its Microsoft Analytics Platform System,
formerly Parallel Data Warehouse). By contrast, its major competitors (IBM, Oracle and SAP) all offer one, as does one new entrant to the Magic Quadrant (Fujitsu).
- Pricing: Microsoft received below-average ratings for pricing suitability, a problem that stems from the pricing model changes
implemented in SQL Server 2012. Microsoft’s cloud offerings appear to be partially mitigating this concern.
- Filemaker, MS SQL & Oracle Comparison
- Gartner’s Magic Quadrant for Operational Database Management Systems
- Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms
Updated on 2015-10-31T23:47:51+00:00, by .