Are You on the Cloud?

I am pretty sure that most of technical people are aware about the technical term "cloud", and even can give some kind of description about what does it mean. The well known association of the cloud computing is with the software as a service, SaaS. However, there are more and more areas of IT services which are moving to the cloud. So, knowing the acronyms for such cases is a part of the IT literacy.

I have filled a survey today "Managing Cloud Applications" posted by the The Office of the CIO®  in collaboration with Katepano SaaS Monitoring and Optimization which reminded me about my intention to create this post and to list all abbreviations.

Here is the list of the cloud services that I am aware of:

PaaS - Platform as a Service
 BaaS - Backup as a Service
BPaaS - Business Process as a Service
CaaS - Communication, Content, and Computing as a Service
DaaS - Database as a Service DaaS ( another one) - Desktop as a Service
IaaS - Infrastructure as a Service
IDaaS -  Identity as a Service
MaaS - Monitoring/Management as a Service
NaaS - Network as a Service
SaaS ( another one) - Storage as a Service
SECaaS - Security as a Service
UCaaS - Unified Communications as a Service
APMaaS - APM (Application Performance Management) as a Service 
LaaS - logging as a service 

Here are some other acronyms that go together with the cloud:
SOA - Service Oriented Architecture
SOCCI - Service Oriented Cloud Computing Infrastructure

As you can see, there are so many IT service already on the cloud that they are even reusing the same surnames. According to industry definition by the National Institute of Standards and Technology, NIST, the "as a service" acronym formed a category XaaS which unites all cloud-related services.

The IaaS was pioneered by Amazon. UCaaS becomes a popular because it is easy to outsource. The MaaS is almost a requirement for IT that uses cloud.  The NaaS is a choice for the mature large companies because they want to get out of the IT business.

According to the market forecasts, by the 2015 year the XaaS market will be more then $40 billions. Microsoft's latest strategy shift to the cloud with its offering of the SkyDrive cloud storage service and cloud-based Office 365 is a strong evidence of the industry shift to the cloud.

So, are you YOU on the cloud? Do you use other then listed above services?


Resources: NETWORK WORLD, August 13, 2012. Volume 29, Number 14.

Information Technology Management: Visualize Your Experience

Information Technology Management: Visualize Your Experience: Do you know that you can present your resume through infographics by using free ans easy tools that pull out info from existing sites.

Visualize Your Experience

Do you know that you can present your resume through infographics by using free ans easy tools that pull out info from existing sites.

Social Media Demographics - infographic

Via: Online MBA Resource social media

Word clouds from the words used on sitecore.net, created with Wordle

Digital presentation of Sitecore on twitter  http://bit.ly/xRXgCJ

Tying Business Intelligence with Business Process Management

Companies are watching carefully, using business intelligence and analytics tools to figure out what’s happening in their markets from the perspective where efficiency can make the difference between profit and loss. The goal is to use right analytics tools to guide business processes changes towards “dramatic productivity enhancing”. This is a responsibility of CIO to establish cooperation between IT department and business units to create a data warehouse and to enable the best use of predictive analytics tools and techniques and tying them with BPM. The metrics are: improvement of financial forecasting, customers retaining and operating profits.


Examples of successful data enabling changes where analytics and BPM are connected:

· The insurance industry – fraud detection;
· Order management, global inventory and invoicing;
· Increasing timing intervals of reports for the decision making produced results allowing adjust business process;
· Analytics tools integrated with customer-relationship management (CRM) or e-commerce systems helps improving processes for engagement with customers;
· Introducing measurements and showing success from the analytics-BPM helps CIO to add more dedicated to analytics staff to their teams.

Companies discover new ways to save:

· Business analytics produced incredible results for CUNA Mutual to open their eyes where that should concentrate their effort to attract new customers. Example: to attract generation Y – build mobile and web products; provide up-sale additional services in convenient way.
· Outsourcing of analytics and data warehousing by using the 3rd party vendor (like Oco) thorough their SaaS tools can resolve a lot of timing issues and save money by providing timely reports and provides for for necessary changes in the business processes. Example: transportation expenses were cut by 12-15%.

Organizations can improve their conversation with customers:

· Many modern BI and analytics tools provide prebuild statistical models which remove the need for highly educated resources and reduce time of the analyses. Example: complex analyses as segmenting customers based not simply on demographics and the products and services they buy, but also on less cut-and-dried information, such as how they behave at a website or what comments they make during call- center interactions .
· Key to game-changing decision making is the ability to detect and respond to market changes, taking into account historical knowledge. Evaluating historical data such as the average annual revenue the customer represents, her payment history and other bought product, and forming the customer value, Direct TV created tactics how to cut churn rates and retain customers.
· Coca Cola created an innovative personalized way of attracting their consumers to interact through the website and provide information about where the products were purchased and offer customers some rewards for that. The company uses this feedback to tailor its pitches and have a relevant dialog with customers.  The company has learned that watching behavior is more meaningful than reading questionnaires Web visitors are asked to fill out. The idea is not just to save business but to create new business.

Analytics tools help companies create more money-generating interactions with customers and shave costs from internal operations. CIOs should connect analytics technologies with ideas about refining business processes.


Resources:  Kim S. Nash, CIO. June 17, 2010. Business Intelligence Meets BPM: Using Data to Change Business Processes on the Fly. Retrieved from www.cio.com

Business Intelligence and Social Media

I have heard different opinions about the value of organizational activities on social medial channels. A lot of advocates (or anti-advocates) see the value of social medias only as another channel to bring visitors to their website.

In such statements at this stage a very important aspect of collecting followers is overlooked. Most of social media website have APIs that let query information about people who are part of your network (your friends, followers, etc.). By privacy policy you can only view the profile of people who allowing queries. A lot of recent software tools exploit this social networking openness. I can see that somebody will come (or already did) with models for  software applications that will do a business intelligence analysis of the data about visitor's behaviour on your website and your activities on social medias, and will provide suggestions how to engage your followers even further.  There will be a clear "aha" moment for your organization how to push social media followers to create a business value for you. Since they are already following you, it means that they are already initiated engagement. Something particular for their needs or interest needs to be done to make them do a second step on the engagement ladder. At some points business intelligence analysis can turn this ladder in the slide.

Very exiting time we are living with the turning point of the web to become a proactive and coming to you with the information you are interested, instead of the current and past way of you going and searching the information on the web. Social media networks are the channels for that, so collect your follower and obtain more!

Data Warehouse

What is a Data Warehouse?

• A pool of data combined from databases across an enterprise to be the source for decision making.
• A repository of current and historical data of potential interest to managers throughout the organization.
• A subject-oriented, integrated, time-variant, nonvolatile collection of data in support of management’s decision-making process.


How does a Data Warehouse differ from a database?

Most operational databases have a product orientation and are tuned to handle transactions that update the database.

What is a Data Mart?

A small warehouse designed for a strategic business unit or a department and is a subset of the datawarehouse.

What is the Data Warehousing process?

Data for the data warehouse is imported from various internal and external resources and is cleaned and organized in a manner consistent with the organization’s needs. After the data is populated in the data warehouse, data mart can be loaded for a specific area or department. Alternatively data mart can be created first and then integrated into an Enterprise Data Warehouse (EDW) if needed.

What are the major components of a data warehouse?

• Data sources
• Data extraction and transformation
• Data loading
• Comprehensive database
• Metadata
• Middleware tools.
 
What are the three steps of the ETL process?

1. Extraction – reading data from one or more databases. Typically all the input data are written to a set of staging tables.

2. Transformation – converting the extracted data from its previous form into the form in which it needs to be so that it can be placed into a data warehouse or simply another database. Transformation occurs by using rules or lookup tables or by combining the data with other data. Any data quality issues pertaining to the source files need to be corrected before the data are loaded to the data warehouse.

3. Load – putting data into the data warehouse.

Why is the ETL process so important for data warehousing effort?

ETL is extremely important for data integration and for providing clean quality data for data warehouse. Quality data becomes a strategic asses for a company.

Abbreviations Used in Business Intelligence

ADS – automated decision systems

ADW - active data warehousing

ANN – artificial neural network

BA – business analytics

BAM – business activity management

BI - business intelligence

BICC – BI Competency Center

BPM – business performance management

BSC - balanced scorecard

CPM – corporate performance management

CRISP-DM - cross-industry standard process for data mining

CSF – critical success factor

DBMS - database management system

DMAIC - define, measure, analyze, improve, control

DSS – decision support system

DW – data warehouse

DWA - data warehouse administrator

EAI - enterprise application integration

EDW – enterprise data warehouse

EII - enterprise information integration

EIS – executive information systems

EPM - enterprise performance management

ETL – extract/transfer/load

GIS – geographical information systems

GUI - graphical user interface

HITS - hyperlink-induced topic search

HOLAP - hybrid OLAP

IPA - intelligent process automation

KDD - knowledge discovery in databases

KMS - knowledge management systems

KPI – key performance indicators

MIS – management information systems

MLP - multi-layered perception

MOLAP- multidimensional OLAP

NLP - natural language processing

ODS - operational data store

OLAP – online analytical processing

OLTP – online transaction processing

PDA – personal digital assistant

PLM - product life cycle management

RDW - real-time data warehousing

ROLAP - Relational OLAP

RDBMS -  relational database management system

SEM - strategic enterprise management

SEMMA - sample, explore, modify, model, assess

SOA - service-oriented integration

SCM – supply chain management

SVD - singular value decomposition

SVM - support vector machines

TDM - term-document matrix

TUN – Teradata University Network (teradatauniversitynetwork.com)



Supporting sites:

teradatauniversitynetwork.com

pearsonhighered.com/turban

information-management.com

tdwi.org – the Data Warehousing institute

olapreport.com

dssresources.com

businessintelligent.ittoolbox.com

b-eye-network.com

aisnet.org
enterprise.waltoncollege.uark.edu/mec.asp

hbsp.harvard.edu/b01/en/academic/edu_home.jhtml

bpir.com

idea-group.com

knowledgestorm.com

cioinsight.com

technologyevaluation.com

baselinemag.com

2012 - The Year of the Big Data

According to the Wall Street Journal columnist DENNIS K. BERMAN, analytics harvesting from massive databases will begin to inform our day-to-day business decisions. He calls it Big Data, analytics, or decision science. Over time, this will significantly change our world. Computer performance power grows so fast, that "systems can now chew through billions of bits of data, analyze them via self-learning algorithms, and package the insights for immediate use." Analytics and self-learning algorithms will be a game changers. An example of the trend is the fact that Hewlett-Packard recently bought Autonomy which has a technical solutions to clean unstructured data and to apply analytics to that big data. It also helps organizations to derive meaning and value from their information. A collection of computer technologies that work with the Big Data are collectively known as Business Intelligence (BI), and also referred to as business analytics.


The importance of analytics is that it help us reduce human biases from our decision-making. Using BI will help us eliminate our worst human tendencies. The key point is to have analytics in a real time. Such information is a must for all types of decisions, for strategic planning and forecasting, and even for survival. Now business cycles become shorter and compressed; that is why faster, more informed, better decision making is a competitive imperative. Organizations have to work smart. A championship of BI become a smart choice for more and more companies.


Examples of how Opera or Mu Sigma helps their customers improve decision making and as a result increase revenue attract venture companies. Investing money in BI becomes very actual due to the fact that there is a whole class of things that couldn't be done five years ago.



Resources: DENNIS K. BERMAN http://online.wsj.com/article/SB10001424052970203462304577138961342097348.html

Organizational Perspective - from good to great.

Does every company has a strategic plan? Is this plan communicated to all level of organization and used for creating operational plans in every department? Are operational plans in every department even exist? A good example would be a marketing department.  If such a plan exist, is it aligned with the organizational strategic plan? Continuing as example with the marketing department, are all activities in the department, and project portfolio are driven by this plan? These are questions that any growing organization starts to ask at some point during its growth.

According to the Organizational Project Management Maturity Model (OPM3), an organizational strategy can turn a good organization into a great one. And of course strategies that fail, or luck of strategy can quickly damage the organization's reputation and brand, internally and externally. "Effective strategy execution is the responsibility of all level of management, who must be involved actively and consistently to orchestrate required organizational changes and to manage the portfolio of investments that underpin these change initiatives."

An organization should have a governance mechanism that force the linkage between strategy and project portfolio. The right governance in project portfolio management provides decision-making transparency and increases likelihood of realizing desired return on investment.

 OPM3 contains the Best Practices designed to help organization to achieve that.

The OPM3 framework contains three interrelated components: Best Practices, Capabilities, and Outcomes.

Best Practices include:

• SMCI Best Practices - Standardize, Measure, Control and continuously Improve
• Organizational Enabler Best Practices - structural, cultural, technological, and human resources.

A Capability is a specific competence that must exist in the organization to be able to execute project management processes. Development of Capabilities leads to Best Practices. These capabilities determine the organizational maturity.

An Outcome is a tangible or intangible result of applying a capability.

OPM3 maturity assessment can help organization to see which Best Practices, Capabilities, and Outcomes an organization has and reveal about the organization's maturity level.  Based on the assessment an organization can create an improvement plan.


Resource: PMI, Organizational Project Management Maturity Model (OPM3), Knowledge Foundation.