Digital presentation of Sitecore on twitter http://bit.ly/xRXgCJ
Tuesday, February 28, 2012
Sunday, February 19, 2012
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
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
Sunday, February 12, 2012
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!
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!
Thursday, February 9, 2012
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?
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?
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.
• 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.
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.
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