Data Analysts, Crystal Reports and Sql Reporting Services Consultants » data analyses

Starring Sakila: Data Warehousing Explained, Illustrated, and Subtitled

admin — Tue, 08 Feb 2011 15:43:43 +0000

Data Analyst

admin — Wed, 02 Jun 2010 17:14:34 +0000

Data Analyst-OPE0000008Q

Description

Company Profile:

Direct Energy is one of North America’s largest energy and energy-related services providers with over 5 million residential and commercial relationships. Direct Energy provides customers with choice and support in managing their energy costs through a portfolio of innovative products and services. A subsidiary of Centrica plc, one of the worlds leading integrated energy companies, Direct Energy operates across Canada, Texas and the northeastern United States.

We continually seek talented people dedicated to providing fresh thinking in an exciting, evolving industry that’s never been more relevant than in today’s global marketplace.

Summary:

This position will be responsible to assist the Management team of Operations on the gathering, reporting, analysis, and explanation of all performance and customer behavioral data. This individual will complete analysis and recommendations on business initiatives, process, policy and technology as related to the achievement of service levels to meet or exceed financial and customer goals. Initiatives or changes will enhance performance to achieve maximum productivity, quality, cost and timeliness. This position will be responsible for data management within the portfolio of credit and collections, live accounts receivable, bad debt control, customer satisfaction and service related to Direct Energy business in Texas.

Key Accountabilities:

Demonstrated expertise on the data analysis for DE Collection to proactively identify business gaps and/or opportunities, facilitate change and resolve issues which impact collection performance at all aspect
Gathers data/information, completes analysis, and recommends new initiatives or amendments to current operating methods with a focus on ‘best in class’ operational processes
Develop & implement tools and processes to extract and manipulate data from various systems / resources including development of ad-hoc reports in order to solve operational issues and/or improve existing processes
Responsible for internal and external reporting with control to accuracy and providing variance explanation, capable to provide recommendation for reporting enhancement
Develop business case and L&G (Loss and Gain) analysis for all recommendations and initiatives
Works closely with team member to leverage expertise and ensure seamless delivery of initiatives on time and within budget
Responsible to monitor and manage accuracy as well as on time delivery for all reports provided by DE external vendors
Interact with cross-functional groups including Sales, Marketing, Finance and Regulatory, to ensure smooth and timely execution of business projects.
Identify and implement policy and process improvements through enhancing existing policies or developing new ones.

Qualifications

Ability to manage and manipulate large amount of data set to provide accurate information to management team at a timely fashion
Knowledge of collection terminology and process within the commodity industry
Ability to develop and maintain business models is an definite asset
2 years of operational experience in collection for the retail commodity (Natural Gas/Electricity) market is an asset.
Proven experience in conflict resolution skills and task priority skills
Ability to work independently, comfortably making rational and reasoned decisions which directly impact corporate revenue, customer service and financial liabilities
Demonstrated advance technical skills with Microsoft Access, Excel, SQL, Power point and ability to develop Macro or VBA
Excellent communication skills (written and verbal)
Strong interpersonal skills and team player
Ability to excel in a fast past, highly volatile environment with self-supervised; effectively managing multiple activities and meeting deadlines
Undergraduate degree in business (B Comm, BA etc) or Statistics

Job Operations Support

Primary LocationCA-ON-Toronto

Schedule Full-time

Flat File data model

admin — Sun, 09 May 2010 04:13:36 +0000

Flat File data model

This post discusses our experience of creating a relational database for company which to store all its information Excel files.

Excel spread sheets is good for analysis purposes like pivot tables, calculations but very inefficient for data storage purpose. We cannot access data easily and compiling reports for operational departments is very complicated.

How to model Flat file into RDBMS? For that reason we have to study business process then design an entity relation diagram. Here is a scenario we aced

The data was extracted from MS Excel flat files then transformed and loaded into MS Access and modeled into RDMS format. Created tables to store Master data about all accounts including customers, suppliers, employees and entity related to Altech business. Designed tables to record financial and material transactions and coordinated with Accounts departments to create general.

In the above case we did the iterative process first excel sheet data was imported MS Access.

Below is simple example to show how falt is modeled into RDBS and its advantages for data storage.

Excel Flat file

Date	Product	Price	Quantity	Total Amount	Customer
1-1-2010	Widget 1	200	3	40	ABC INC, Louisiana
1-2-201	Widget 2	3000	2	6000	XYZ Company

Products table

Prid	Name	Suggested Price
1	Widget 1	200
Customer Table
Cust ID	Name	Address
1	ABC INC	Lousian, New Orleans

Sales transaction in RDBMS format

Date	Product id	Customer ID	Qty sold	Sale Price
1-1-2010	1	1	2	200

Additional tables were created to break up the one single large table.

Created customers table to hold their master data.

Created products table to hold their master data

Created transaction table business transaction like sales to customers.

Advantages of storing data in RDBMS.

1-In flat file if the customer move we have to change address in every transaction stored in Excel Sheet. In RDBMS if change address in master database of customer table we do not have to change address in every sales transaction because they transaction store the customer id which is foriegn key in transaction table.

2- Fast data entry

3- easy management of data

4- flexible reporting.

5-If want to analyze the data the data from RDBMS can be exported into Excel files for analyses purposes.

Sample: Specific Job Skills for data analyst

admin — Mon, 22 Mar 2010 20:59:23 +0000

Database professionals like sql developer, reporting analysts in Crystal Reports, Sql Reporting services and sql programmers can enter into new promising field of healthcare data analysts by following the job descriptions in this field. Following is the sample job description from – The Washington State Hospital Association (WSHA) published on Jan 2010.

Data profeDemonstrated experience and expertise with SAS programming language required.
Demonstrated experience using advanced Excel features and techniques required. Demonstrated experience in analysis and presentation of data required. Experience working with a variety of information systems and data files, including large and complex files: analyzing file structure, using and creating file layouts, transforming raw data into finished products. Familiarity with various types and sources of health care information, including financial and patient-level data files.

Familiarity with Washington State Comprehensive Hospital Abstract Reporting System (CHARS) desirable.
Experience with database application development (e.g., Microsoft Access) desirable. Strong communication skills, both written and spoken. Comfortable working independently, with experience working in a team environment. Skills in establishing and maintaining effective working relationships with WSHA members and staff. Physical ability to use computer hardware and software required. Ability to read, write, speak and understand English required. Educational, Experience and/or Licensing Requirements

Bachelor’s degree or higher in relevant field.
Undergraduate or graduate coursework in statistics, data analysis, research methods.
2-5 years experience in data analysis, decision support, including demonstrated proficiency with analytical software.

Data Steward Role & Responsibilities

admin — Tue, 16 Mar 2010 21:57:58 +0000

Data Stewards act as the conduit between IT and the business and accept accountability for data definition, data management process definition, and information quality levels for specific data subject areas. Data stewardship involves managing the enterprise’s data assets in order to improve their reusability, accessibility, and quality.

Data stewardship involves taking responsibility for data elements for their end-to-end usage across the enterprise. Data stewardship does not involve just a single role but includes a network of personnel with accountabilities for ensuring that all aspects of an effective information development program are being accomplished.

Data Stewardship is an ongoing activity that spans all competencies of all individuals within an organisation. Read More

A data steward ensures that each assigned data element:

1. Has clear and unambiguous data element definition.
2. Does not conflict with other data elements in the metadata registry (removes duplicates, overlap etc.)
3. Has clear enumerated value definitions if it is of type Code.
4. Is still being used (remove unused data elements)
5. Is being used consistently in various computer systems
6. Has adequate documentation on appropriate usage and notes
7. Documents the origin and sources of authority on each metadata element

Benefits of Data Stewardship

1. Consistent use of data management resource
2. Easy mapping of data between computer systems and exchange documents
3. Lower costs associated with migration to Service Oriented Architecture (SOA)

data masking

admin — Fri, 12 Mar 2010 19:03:35 +0000

This post is about data masking a role we read in a job description.

Effective data masking requires data to be altered in a way that the actual values cannot be determined or reengineered, functional appearance is maintained, so effective testing is possible. Data can be encrypted and decrypted, relational integrity is maintained, security polices can be established and separation of duties between security and administration established. Common methods of data masking include: encryption/decryption, shuffling, masking (i.e. numbers letters), substitution (i.e. All female names = Julie), nulling (####) or shuffling (zip code12345 = 53412).

In future posts we write more on this topic.
Source: Wikipedia.org

Creating Data Mart by Consolidating Multi-Source Enterprise Operational Data

admin — Wed, 10 Mar 2010 22:28:54 +0000

We have included a very practical Paper on Data Mart by J. D. D. Daniel, K. N. Goh, and S. M. Yusop.

Abstract – Trends in business intelligence, e-commerce and remote access make it necessary and practical to store data in different ways on multiple systems with different operating systems. As business evolve and grow, they require efficient computerized solution to perform data update and to access data from diverse
enterprise business applications.

The objective of this paper is to demonstrate the capability of DTS [1] as a database solution for automatic data transfer and update in solving business problem. This DTS package is developed for the sales of variety of plants and eventually expanded into commercial supply and landscaping business.

Dimension data modeling is used in DTS package to extract, transform and load data from heterogeneous database systems such as MySQL, Microsoft Access and Oracle that consolidates into a Data Mart residing in SQL Server. Hence, the data transfer from various databases is scheduled to run automatically every quarter of the year to review the efficient sales analysis. Therefore, DTS is absolutely an attractive solution for automatic data transfer and update which meeting today’s business needs.

Please read the complete Paper

Rules and Check constraint

admin — Sun, 07 Mar 2010 20:45:01 +0000

Rules are a backward-compatibility feature that perform some of the same functions as CHECK constraints. CHECK constraints are the preferred, standard way to restrict the values in a column. CHECK constraints are also more concise than rules; there can only be one rule applied to a column, but multiple CHECK constraints can be applied. CHECK constraints are specified as part of the CREATE TABLE statement, while rules are created as separate objects and then bound to the column.

This example creates a rule that performs the same function as the CHECK constraint example in the preceding topic. The CHECK constraint is the preferred method to use in Microsoft® SQL Server™ 2000.

CREATE RULE id_chk AS @id BETWEEN 0 and 10000
GO
CREATE TABLE cust_sample
(
cust_id int
PRIMARY KEY,
cust_name char(50),
cust_address char(50),
cust_credit_limit money,
)
GO
sp_bindrule id_chk, ‘cust_sample.cust_id’
GO

Sourec: Sql Server 2000 books online

Difference between Index and Primary Key

admin — Sun, 07 Mar 2010 20:21:16 +0000

This post is on very important topic – “Difference between Index and Key” and is explained in very clear and easy terms by Michael J. Hernandez in his book Database Design for Mer Mortals on page 61. We are emphasizing in this post that most of the IT books lacks clarity or makes concepts more complicated resultantly negative impact on the productivity and probably should look at the above book how it explains an important topic.

An index is a structure RDBMS provides to improves the data processing. Your particular RDBMS program will determine how the index works and how you use it. How index has absolutely nothing to do with logical data structure and people often confuse it with term key.

Index and key are just two more terms that are widely and frequently misused throughout the database industry and in numerous database related publications – you’ll always know the difference between the two if you remember that keys are logical structures you use to identify records within a table and indexes are physical structures you use to optimize data processing.

IBM Cognos solutions for business analytics

admin — Thu, 04 Mar 2010 20:13:47 +0000

Because midsize businesses are the engines of a Smarter Planet™, IBM has designed a business analytics solution for organizations like yours.

The IBM Cognos Express solution helps C-level executives and other business users create reports, analyze data and identify trends quickly—with no special training or IT involvement—using dashboards, gauges and other visual tools. You can get started with the IBM Cognos Express business analytics solution in about an hour and follow these steps to a more profitable bottom line:

Unlock data across your organization.
Uncover new insights.
Take action to drive business performance.

Learn more and register for the IBM Cognos Midsize Business Analytics Virtual Summit, March 11 at 11:00 AM or 8:00 PM ET.