| DataWarehouse Designer |
| Eagle Professional Resources -CALGARY,AB Jobs |
| DataWarehouse Designer Calgary, AB Date Posted: April 18, 2012 Job ID: 22430 Job Description Eagle is currently seeking one (1) DataWarehouse Designer. This contract opportunity is slated to begin in... Resources Eagle Professional Resources DataWarehouse Designer Jobs .... Job Details |
| Found at Eagle Professional Resources on 19 Apr 2012 -- Save Job |
| Datawarehouse Analyst - Informatica ETL Developer |
| Inteqna -CALGARY,AB Jobs |
| Datawarehouse Analyst - Informatica ETL Developer Employment: Contract Posted On: Tuesday, April 17, 2012 # of Openings: 1 Classification: Location: Calgary, AB Apply To: Description: INTEQNA is... Organizations or equivalent endeavours. Inteqna Inteqna Datawarehouse Analyst - Informatica ETL Developer .... Job Details |
| Found at Inteqna on 18 Apr 2012 -- Save Job |
| Senior Programmer, Datawarehouse (DB2, Unix Shell Scripting |
| Scotiabank -TORONTO,ON Jobs |
| , Datawarehouse to support Finance and Global Risk Management business lines. The incumbent will have at least 7... agencies please. Scotiabank Scotiabank Senior Programmer, Datawarehouse (DB2, Unix Shell Scripting .... Job Details |
| Found at Scotiabank on 02 Apr 2012 -- Save Job |
| Datawarehouse Analyst/Designer & ETL Developer |
| West Works Group -CALGARY,AB Jobs |
| Datawarehouse Analyst/Designer & ETL Developer - West Works Group Inc. - BCjobs.ca .list-row-grey... Profile Job Seeking Advice Job Folder Loading... Job Description Datawarehouse Analyst/Designer & ETL...: Datawarehouse Analyst/Designer & ETL Developer Reference ID: 4481686 - JSWW1311 Company: West Works Group .... Job Details |
| Found at BC Jobs (bcjobs.ca) on 16 Apr 2012 -- Save Job |
| Senior Programmer, Datawarehouse (DB2, Unix Shell Scripting), SCOTIABANK |
| Scotiabank -TORONTO,ON Jobs |
| Senior Programmer, Datawarehouse (DB2, Unix Shell Scripting), SCOTIABANK Toronto, ON, CANADA Posted... Programmer, Datawarehouse to support Finance and Global Risk Management business lines. The incumbent... Scotiabank Workopolis Senior Programmer, Datawarehouse (DB2, Unix Shell Scripting), SCOTIABANK .... Job Details |
| Found at Workopolis on 29 Mar 2012 -- Save Job |
| ETL/Informatica Developer |
| Modis Canada -BURNABY,BC Jobs |
| Canada. The Datawarehouse team is looking forward to fill one the DW/ETL/Informatica Developer role for .... Job Details |
| Found at Modis on 31 Mar 2012 -- Save Job |
| BI Consultant |
| SI Systems -TORONTO,ON Jobs |
| Requirements (Mandatory) Please comment on any experience you have working with DataWarehouse and/OR .... Job Details |
| Found at SI Systems on 13 Apr 2012 -- Save Job |
| BI/DW Architect (SAP BW/BO) |
| GSI Consulting -CALGARY,AB Jobs |
| DataWarehouse Workbench Completed several Business Intelligence project life-cycles Expertise in Information .... Job Details |
| Found at GSI Consulting on 31 Mar 2012 -- Save Job |
| C# Technical Lead-Loans/Responsable technique C#, Prêts |
| Morgan Stanley -MONTREAL,QC Jobs |
| historical datawarehouse The focus of this technology role will include : - Leading a core team of .... Job Details |
| Found at Morgan Stanley on 13 Apr 2012 -- Save Job |
| DBA (database analyst) (Data Warehouse & Analyst Lead) |
| Shopify -OTTAWA,ON Jobs |
| experience with Datawarehouse systems, UML, JavaScript, Ruby on Rails & PHP Employer: Shopify Inc .... Job Details |
| Found at Jobbank on 25 Apr 2012 -- Save Job (Deadline: 15 May 2012) |
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PostData Warehousing - Tips from the Trenches
These
tips have been developed over the course of my career in data
warehousing. They span information and lessons learned from multiple
clients across multiple industries. New tips as they are developed will
be added so be sure to check back often for new tips!
Never underestimate the complexity of a source system
Many data warehousing projects never fully appreciate the complexity of a source system until it is too late, which forces architecture changes late in development or data quality issues found after deployment. Often times ETL developers are pointed towards some source system tables and given no data dictionaries, no time to do substantial data analysis including data profiling and no SME from the source system owner. This is becoming increasingly common in larger enterprise organizations where distinct data warehousing groups exist seperated from the source system applications.
Obtain proper business requirements to guide development of data warehouse
Very rarely will building a data warehouse without proper requirements be successfull. However it is commonly done, especially in situations where IT feels it cannot wait for business requirements or that IT feels the business is going to want everything so lets just bring everything into the data warehouse. The end result is that the data warehouse team is tasked with too large of a project with no real clear direction or end. Issues also result from not knowing how the business wants to use the data which often leads to issues surrounding data quality, grain, implied relationships and calculations/derivations. Proper requirements are mandatory in every other IT project don't make them optional in building your data warehouse.
The data warehouse can't do all of the integration
If source systems put little to no effort into integratin then the job to further integrate data in the data warehouse is very difficult. The integration between multiple source systems at the data layer often makes it extremely difficult or impossible for the data warehouse to complete the integration process. Often times a tight integration at the application layer exists but at the data layer many of the details behind that integration are lost. Source systems are usually concerned with getting the data they need right now and are not concerned with how a data warehousing application might need the data in the future. The better that source system integration is the better data quality will be in the data warehouse and one of the primary costs of building a data warehouse which is data integration goes down signficantly.
Never underestimate the complexity of a source system
Many data warehousing projects never fully appreciate the complexity of a source system until it is too late, which forces architecture changes late in development or data quality issues found after deployment. Often times ETL developers are pointed towards some source system tables and given no data dictionaries, no time to do substantial data analysis including data profiling and no SME from the source system owner. This is becoming increasingly common in larger enterprise organizations where distinct data warehousing groups exist seperated from the source system applications.
Obtain proper business requirements to guide development of data warehouse
Very rarely will building a data warehouse without proper requirements be successfull. However it is commonly done, especially in situations where IT feels it cannot wait for business requirements or that IT feels the business is going to want everything so lets just bring everything into the data warehouse. The end result is that the data warehouse team is tasked with too large of a project with no real clear direction or end. Issues also result from not knowing how the business wants to use the data which often leads to issues surrounding data quality, grain, implied relationships and calculations/derivations. Proper requirements are mandatory in every other IT project don't make them optional in building your data warehouse.
The data warehouse can't do all of the integration
If source systems put little to no effort into integratin then the job to further integrate data in the data warehouse is very difficult. The integration between multiple source systems at the data layer often makes it extremely difficult or impossible for the data warehouse to complete the integration process. Often times a tight integration at the application layer exists but at the data layer many of the details behind that integration are lost. Source systems are usually concerned with getting the data they need right now and are not concerned with how a data warehousing application might need the data in the future. The better that source system integration is the better data quality will be in the data warehouse and one of the primary costs of building a data warehouse which is data integration goes down signficantly.
Data Warehouse Architect Job Interview Questions 2
This position is a more senior database developer role and is
required to lead projects. Tell us about the most challenging project
you have successfully lead data warehousing implementations? What were
some of the challenges?
Have you been responsible for establishing the long-term strategy and technical architecture as well as the short-term scope for a multi-phased data warehouse effort? Please describe?
Database developers often work in development teams. Give us an example of some challenges you have had working in or being part of a database development team? What were some of the challenges and how did you resolve them?
We are looking for a database developer with a deep knowledge in data architecture. What is your knowledge of the various data architectures and methodologies including all of the many nuances like meta data, performance management, data quality, schema development, mart vs. data warehouse issues etc.? Give us some examples of how you have used these in the past?
How do you keep track of the direction of the data warehouse architectural program? How do you ensure program compliance and flexibility for exceptions and change?
Do you have work experience with the following? please describe?:
-Enterprise Data Warehouse Architecture
-Dimensional Data Modeling
-Data Profiling and Master Data Management
-Informatica – ETL tool
-Oracle, SQL and DB2 are
-ERWin modeling
-Database Hierarchy Management
-Star Schema
-C-MDM
How Did We Create These Questions and How Should You Answer?
The interview questions you see above, are created using the same methods we used as corporate HR professionals. For more information on how we create these questions and how to answer them see the post, “Soft Skills Sells In Interviews”
Have you been responsible for establishing the long-term strategy and technical architecture as well as the short-term scope for a multi-phased data warehouse effort? Please describe?
Database developers often work in development teams. Give us an example of some challenges you have had working in or being part of a database development team? What were some of the challenges and how did you resolve them?
We are looking for a database developer with a deep knowledge in data architecture. What is your knowledge of the various data architectures and methodologies including all of the many nuances like meta data, performance management, data quality, schema development, mart vs. data warehouse issues etc.? Give us some examples of how you have used these in the past?
How do you keep track of the direction of the data warehouse architectural program? How do you ensure program compliance and flexibility for exceptions and change?
Do you have work experience with the following? please describe?:
-Enterprise Data Warehouse Architecture
-Dimensional Data Modeling
-Data Profiling and Master Data Management
-Informatica – ETL tool
-Oracle, SQL and DB2 are
-ERWin modeling
-Database Hierarchy Management
-Star Schema
-C-MDM
How Did We Create These Questions and How Should You Answer?
The interview questions you see above, are created using the same methods we used as corporate HR professionals. For more information on how we create these questions and how to answer them see the post, “Soft Skills Sells In Interviews”
Data Warehouse Architect Job Interview Questions
A Data Warehouse Architect describes the principles which govern the
creation of a solution on a technical level. Basically, the database
developer produces a description of the complete solution, linking
technical implementation to business needs. If you are a Data Warehouse
Architect and not sure what job interview questions may be asked in the
interview? We have created potential Data Warehouse Architect interview
questions that may be asked in your next job interview.
Depending on the company, industry and so forth, Data Warehouse Architect may also be called:
Depending on the company, industry and so forth, Data Warehouse Architect may also be called:
- data administrator
- database developer
- data custodian
- data dictionary administrator
- data warehouse analyst
- database administrator (DBA)
- database analyst
- database architect
- technical architect – database
Data Warehouse :: Data Warehousing Job Interview Questions and Answers
Data Warehousing Interview Questions and Answers will guide now that Data warehouse is a repository of an organizations electronically stored data. Data warehouses are especially designed to facilitate reporting and analysis about the data of any organization. So learn Data Warehousing concepts by Data Warehousing Interview Questions and Answers and get preparation of Data Warehousing Jobs Interview.
1 What is Meta data?
2 Briefly state different between data ware house & data mart?
3 What is galaxy schema?
4 Suppose you are filtering the rows using a filter transformation only the rows meet the condition pass to the target. Tell me where the rows will go that does not meet the condition.
5 After we create a SCD table, can we use that particular Dimension as a dimension table for Star Schema?
6 What is Core Dimension?
7 How much data hold in one universe.
8 Can any one explain about Core Dimension, Balanced Dimension, and Dirty Dimension?
9 Can any one explain the Hierarchies level Data warehousing.
10 What is data cleaning? How can we do that?
11 What is dimension modeling?
12 Where the cache files stored?
13 How can you import tables from a database?
14 What is drilling across?
15 How Many different schemas or DW Models can be used in Siebel Analytics. I know Only STAR and SNOW FLAKE and any other model that can be used?
16 What is an error log table in Informatica occurs and how to maintain it in mapping?
17 What is loop in Data warehousing?
18 How many clustered indexes can u create for a table in DWH? In case of truncate and delete command what happens to table, which has unique id.
19 What is hybrid slowly changing dimension?
20 Can a dimension table contain numeric values?
21 How do you create Surrogate Key using Ab Initio?
22 What is the difference between star and snowflake schemas?
23 What is a CUBE in data warehousing concept?
24 What is the difference between Snowflake and Star Schema? What are situations where Snowflake Schema is better than Star Schema when the opposite is true?
25 What is ER Diagram?
26 What is degenerate dimension table?
27 What is VLDB?
28 What is Dimensional Modeling?
29 What are the various ETL tools in the Market?
30 What are the possible data marts in Retail sales?
31 What is meant by metadata in context of a Data warehouse and how it is important?
32 What is a linked cube?
33 What is surrogate key? Where we use it? Explain with examples.
34 What are the data types present in BO? What happens if we implement view in the designer n report?
35 What are data validation strategies for data mart validation after loading process?
36 What is Data warehousing Hierarchy?
37 What is BUS Schema?
38 What are the methodologies of Data Warehousing?
39 What is conformed fact?
40 What is Difference between E-R Modeling and Dimensional Modeling?
41 Why fact table is in normal form?
42 What is junk dimension? What is the difference between junk dimension and degenerated dimension?
43 What is the main difference between Inmon and Kimball philosophies of data warehousing?
44 What is the difference between view and materialized view?
45 What is the advantages data mining over traditional approaches?
46 What are the steps to build the data warehouse?
47 What is the data type of the surrogate key?
48 What is a source qualifier?
49 What do you mean by static and local variable?
50 What are the different types of data warehousing?
51 What are Fact, Dimension, and Measure?
52 What is the data type of the surrogate key?
53 What are Data Marts?
54 What are the differences between star and snowflake schema?
55 What is a cube in data warehousing concept?
56 What are the difference between Snow flake and Star Schema? What are situations where Snow flake Schema is better than Star Schema to use and when the opposite is true?
57 What is Dimensional Modelling?
58 What is Log Switch?
59 What is On-line Redo Log?
60 Which parameter specified in the DEFAULT STORAGE clause of CREATE TABLESPACE cannot be altered after creating the table space?
61 What are the steps involved in Database Startup?
62 What are the steps involved in Instance Recovery?
63 Can Full Backup be performed when the database is open?
64 What are the different modes of mounting a Database with the Parallel Server?
65 What are the advantages of operating a database in ARCHIVELOG mode over operating it in NO ARCHIVELOG mode?
66 What are the steps involved in Database Shutdown?
67 What is Archived Redo Log?
68 What is Restricted Mode of Instance Startup?
69 What is Partial Backup?
70 What is Mirrored on-line Redo Log?
71 What is a full backup?
72 Can a View based on another View?
73 Can a Table space hold objects from different Schemes?
74 Can objects of the same Schema reside in different table spaces?
75 What is the use of Control File?
76 Do you View contain Data?
77 What are the Referential actions supported by FOREIGN KEY integrity constraint?
78 What are the types of Synonyms?
79 What is a Redo Log?
80 What is an Index Segment?
81 Explain the relationship among Database, Table space and Data file?
82 What are the different types of Segments?
83 What are Clusters?
84 What is an Integrity Constrains?
85 What is an Index?
86 What is an Extent?
87 What is a View?
88 What is Table?
89 What is schema?
90 Describe Referential Integrity?
91 What is a Hash Cluster?
92 What is a Private Synonyms?
93 What is Database Link?
94 What is a Table space?
95 What is Rollback Segment?
96 What are the Characteristics of Data Files?
97 How do you define Data Block size?
98 What does a Control file Contain?
99 What is the effect of setting the value "CHOOSE" for OPTIMIZER_GOAL, parameter of the ALTER SESSION Command?
100 What is the function of Optimizer?
101 What is Execution Plan?
102 What are the different approaches used by Optimizer in choosing an execution plan?
103 What is the difference between OLAP and OLTP?
104 What is the difference between aggregate table and materialized view?
105 "A dimension table is wide but the fact table is deep," Explain the statement in your own words.
106 What is a data profile?
107 Explain the advantages of RAID 1, 1/0, and 5. what type of RAID setup would you put your TX logs.
108 What is the difference between mapping parameter & mapping variable in data warehousing?
109 What is the difference between metadata and data dictionary?
110 What is Virtual Data Warehousing?
111 Which technology should be used for interactive data querying across multiple dimensions for a decision making for a DW?
112 What is the difference between dependent data warehouse and independent data warehouse?
113 What is the main difference between star and snowflake star schema? Which one is better and why?
114 What is critical column?
115 How can you implement many relations in star schema model?
116 Where the Data cube technology is used?
117 Can you pass sql queries in filter transformation?
118 After the complete generation of a report who will test the report and who will analyze it?
119 After the generation of a report to whom we have to deploy or what we do after the completion of a report?
120 What is "method/1"?
121 What are data modeling and data mining? Where it will be used?
122 What is data analysis? Where it will be used?
123 What is data warehouse architecture?
124 What is Informatica Architecture?
125 What is unit testing?
126 What is type 2 version dimension?
127 For faster process, what we will do with the Universe?
128 I have two Universes created by two difference database can we join them in Designer & Report level? How
129 What is difference between drill & scope of analysis?
130 What is a real-time data warehouse? How is it different from near to real-time data warehouse?
131 How can we run the graph? What is the procedure for that? How can we schedule the graph in UNIX?
1 What is Meta data?
2 Briefly state different between data ware house & data mart?
3 What is galaxy schema?
4 Suppose you are filtering the rows using a filter transformation only the rows meet the condition pass to the target. Tell me where the rows will go that does not meet the condition.
5 After we create a SCD table, can we use that particular Dimension as a dimension table for Star Schema?
6 What is Core Dimension?
7 How much data hold in one universe.
8 Can any one explain about Core Dimension, Balanced Dimension, and Dirty Dimension?
9 Can any one explain the Hierarchies level Data warehousing.
10 What is data cleaning? How can we do that?
11 What is dimension modeling?
12 Where the cache files stored?
13 How can you import tables from a database?
14 What is drilling across?
15 How Many different schemas or DW Models can be used in Siebel Analytics. I know Only STAR and SNOW FLAKE and any other model that can be used?
16 What is an error log table in Informatica occurs and how to maintain it in mapping?
17 What is loop in Data warehousing?
18 How many clustered indexes can u create for a table in DWH? In case of truncate and delete command what happens to table, which has unique id.
19 What is hybrid slowly changing dimension?
20 Can a dimension table contain numeric values?
21 How do you create Surrogate Key using Ab Initio?
22 What is the difference between star and snowflake schemas?
23 What is a CUBE in data warehousing concept?
24 What is the difference between Snowflake and Star Schema? What are situations where Snowflake Schema is better than Star Schema when the opposite is true?
25 What is ER Diagram?
26 What is degenerate dimension table?
27 What is VLDB?
28 What is Dimensional Modeling?
29 What are the various ETL tools in the Market?
30 What are the possible data marts in Retail sales?
31 What is meant by metadata in context of a Data warehouse and how it is important?
32 What is a linked cube?
33 What is surrogate key? Where we use it? Explain with examples.
34 What are the data types present in BO? What happens if we implement view in the designer n report?
35 What are data validation strategies for data mart validation after loading process?
36 What is Data warehousing Hierarchy?
37 What is BUS Schema?
38 What are the methodologies of Data Warehousing?
39 What is conformed fact?
40 What is Difference between E-R Modeling and Dimensional Modeling?
41 Why fact table is in normal form?
42 What is junk dimension? What is the difference between junk dimension and degenerated dimension?
43 What is the main difference between Inmon and Kimball philosophies of data warehousing?
44 What is the difference between view and materialized view?
45 What is the advantages data mining over traditional approaches?
46 What are the steps to build the data warehouse?
47 What is the data type of the surrogate key?
48 What is a source qualifier?
49 What do you mean by static and local variable?
50 What are the different types of data warehousing?
51 What are Fact, Dimension, and Measure?
52 What is the data type of the surrogate key?
53 What are Data Marts?
54 What are the differences between star and snowflake schema?
55 What is a cube in data warehousing concept?
56 What are the difference between Snow flake and Star Schema? What are situations where Snow flake Schema is better than Star Schema to use and when the opposite is true?
57 What is Dimensional Modelling?
58 What is Log Switch?
59 What is On-line Redo Log?
60 Which parameter specified in the DEFAULT STORAGE clause of CREATE TABLESPACE cannot be altered after creating the table space?
61 What are the steps involved in Database Startup?
62 What are the steps involved in Instance Recovery?
63 Can Full Backup be performed when the database is open?
64 What are the different modes of mounting a Database with the Parallel Server?
65 What are the advantages of operating a database in ARCHIVELOG mode over operating it in NO ARCHIVELOG mode?
66 What are the steps involved in Database Shutdown?
67 What is Archived Redo Log?
68 What is Restricted Mode of Instance Startup?
69 What is Partial Backup?
70 What is Mirrored on-line Redo Log?
71 What is a full backup?
72 Can a View based on another View?
73 Can a Table space hold objects from different Schemes?
74 Can objects of the same Schema reside in different table spaces?
75 What is the use of Control File?
76 Do you View contain Data?
77 What are the Referential actions supported by FOREIGN KEY integrity constraint?
78 What are the types of Synonyms?
79 What is a Redo Log?
80 What is an Index Segment?
81 Explain the relationship among Database, Table space and Data file?
82 What are the different types of Segments?
83 What are Clusters?
84 What is an Integrity Constrains?
85 What is an Index?
86 What is an Extent?
87 What is a View?
88 What is Table?
89 What is schema?
90 Describe Referential Integrity?
91 What is a Hash Cluster?
92 What is a Private Synonyms?
93 What is Database Link?
94 What is a Table space?
95 What is Rollback Segment?
96 What are the Characteristics of Data Files?
97 How do you define Data Block size?
98 What does a Control file Contain?
99 What is the effect of setting the value "CHOOSE" for OPTIMIZER_GOAL, parameter of the ALTER SESSION Command?
100 What is the function of Optimizer?
101 What is Execution Plan?
102 What are the different approaches used by Optimizer in choosing an execution plan?
103 What is the difference between OLAP and OLTP?
104 What is the difference between aggregate table and materialized view?
105 "A dimension table is wide but the fact table is deep," Explain the statement in your own words.
106 What is a data profile?
107 Explain the advantages of RAID 1, 1/0, and 5. what type of RAID setup would you put your TX logs.
108 What is the difference between mapping parameter & mapping variable in data warehousing?
109 What is the difference between metadata and data dictionary?
110 What is Virtual Data Warehousing?
111 Which technology should be used for interactive data querying across multiple dimensions for a decision making for a DW?
112 What is the difference between dependent data warehouse and independent data warehouse?
113 What is the main difference between star and snowflake star schema? Which one is better and why?
114 What is critical column?
115 How can you implement many relations in star schema model?
116 Where the Data cube technology is used?
117 Can you pass sql queries in filter transformation?
118 After the complete generation of a report who will test the report and who will analyze it?
119 After the generation of a report to whom we have to deploy or what we do after the completion of a report?
120 What is "method/1"?
121 What are data modeling and data mining? Where it will be used?
122 What is data analysis? Where it will be used?
123 What is data warehouse architecture?
124 What is Informatica Architecture?
125 What is unit testing?
126 What is type 2 version dimension?
127 For faster process, what we will do with the Universe?
128 I have two Universes created by two difference database can we join them in Designer & Report level? How
129 What is difference between drill & scope of analysis?
130 What is a real-time data warehouse? How is it different from near to real-time data warehouse?
131 How can we run the graph? What is the procedure for that? How can we schedule the graph in UNIX?
Software Developer vs Data Warehouse
Hi,
I am a graduate student confused between what field to go for ? To get trained as a C#,.NET developer or to work as a contractor in the field of Data Warehousing. I look more towards a job which is safer. Please give your comments.
Thanks
Pulki
I am a graduate student confused between what field to go for ? To get trained as a C#,.NET developer or to work as a contractor in the field of Data Warehousing. I look more towards a job which is safer. Please give your comments.
Thanks
Pulki
Building a data warehouse in SQL Server: Eight tips to get started
When building a data warehouse using SQL Server technologies, there are some challenges you
might face. I'll offer you some suggestions for overcoming them. Naturally, each environment is
likely to add its own twist to the challenges of building a data warehouse, but most of these
issues are generic enough to apply to many companies embarking on architecting business
intelligence (BI) applications.
Management support. This is the first and foremost challenge you must overcome. It is annoying to technical people (including yours truly) because it has to do with politics and not software. Let's keep in mind who signs your paycheck, however. If management isn't convinced they need a data warehouse all your technical skills will be in vain. Unfortunately upper management often thinks of a data warehouse as yet another system they have to invest in without any immediate return. Your job is to convince the powers that be they're not paying for bells and whistles – data warehouse will help them make better, more informed decisions by correlating data scattered across the enterprise. It is not uncommon to totally change the way an organization operates after a data warehouse application is implemented. Sometimes it helps to build a proof-of-a-concept (POC) project to demonstrate the power of BI. POC data warehouse will only contain a small portion of all data
Management support. This is the first and foremost challenge you must overcome. It is annoying to technical people (including yours truly) because it has to do with politics and not software. Let's keep in mind who signs your paycheck, however. If management isn't convinced they need a data warehouse all your technical skills will be in vain. Unfortunately upper management often thinks of a data warehouse as yet another system they have to invest in without any immediate return. Your job is to convince the powers that be they're not paying for bells and whistles – data warehouse will help them make better, more informed decisions by correlating data scattered across the enterprise. It is not uncommon to totally change the way an organization operates after a data warehouse application is implemented. Sometimes it helps to build a proof-of-a-concept (POC) project to demonstrate the power of BI. POC data warehouse will only contain a small portion of all data
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