1. Data Cube and OLAP Server
Madhavi Gundavarapu

2. Data Cube and OLAP Server
Outline
What is Data Analysis?
Steps in Data Analysis
SQL-92 Aggregate Functions
Limitations of GROUP BY
OLAP Server
CUBE Operator
ROLLUP Operator
Madhavi Gundavarapu
Data Cube and OLAP Server

3. Data Cube and OLAP Server
What is Data Analysis?
DATA
ANALYSIS
query
exact
response
User issues a query, receives a response and formulates the next query based on the response
This process repeats until the user gets the required result
Fundamentally an iterative process
Hello mahesh
Madhavi Gundavarapu
Data Cube and OLAP Server

4. Data Cube and OLAP Server
Why Data Analysis?
Search for unusual patterns of data
Summarize data values
Extract statistical information
Contrast one category with another
Provide a consolidated view of enterprise data buried in OLTP databases
Help Decision makers understand business trends
Derive intelligible results from ad hoc, voluminous and scattered data
Hello mahesh
Madhavi Gundavarapu
Data Cube and OLAP Server

5. Data Cube and OLAP Server
Steps in Data Analysis
Formulate query
Extract aggregated data
Visualize results
Analyze
Analyze &
Formulate
Extract
Visualize
Madhavi Gundavarapu
Data Cube and OLAP Server

6. Data Cube and OLAP Server
Overview of SQL-92
SQL has several aggregate operators:
sum(), count(), avg(), min(), max()
The basic idea is:
Combine all values in a column
into a single scalar value
Syntax
SELECT sum(units)
FROM inventory;
Madhavi Gundavarapu
Data Cube and OLAP Server

7. Overview of SQL-92 (contd.): Distinct Clause
Allows aggregation over distinct values
Example
SELCT COUNT(DISTINCT locations)
FROM inventory;
Madhavi Gundavarapu
Data Cube and OLAP Server

8. Overview of SQL-92 (contd.): GROUP BY Clause
Group By allows aggregates over table sub-groups
Result is a new table
Syntax:
SELCT location, sum(units)
FROM inventory
GROUP BY location
HAVING nation = “USA”;
Madhavi Gundavarapu
Data Cube and OLAP Server

9. Limitations of GROUP BY
Users want CrossTabs
GROUP BY is limited to 0-D and 1-D aggregates
Users want sub-totals and totals
drill-down & roll-up reports
M T W T F S S
AIR
HOTEL
FOOD
MISC
sum
Madhavi Gundavarapu
Data Cube and OLAP Server

10. Multidimensional Data
Measure Attributes
Dimension Attributes
Example
Madhavi Gundavarapu
Data Cube and OLAP Server

11. Data Cube and OLAP Server
OLAP System
On-Line Analytical Processing System
Interactive system
Permits analysts to view summaries of multidimensional data
On-Line indicates
No long waits to see result of a query
response times within a few seconds for new summaries
View data at different levels of granularity
Madhavi Gundavarapu
Data Cube and OLAP Server

12. Data Cube and OLAP Server
SQL:1999 OLAP Extensions
SQL-92 functionality was limited
SQL:1999 standard defines
CUBE
ROLLUP
as generalizations of GROUP BY clause
Madhavi Gundavarapu
Data Cube and OLAP Server

13. CUBE : Relational Aggregate Operator
N-dimensional generalization of simple aggregate functions
CHEVY
FORD
1990
1991
1992
1993
RED
WHITE
BLUE
By Color
By Make & Color
By Make & Year
By Color & Year
By Make
By Year
Sum
The Data Cube and
The Sub-Space Aggregates
Chevy
Ford
Cross Tab
Group By
(with total)
Aggregate
The CUBE operator is the N-dimensional generalization of simple aggregate functions. The 0D data cube is a point. The 1D data cube is a line with a point. The 2D data cube is a cross tabulation, a plane, two lines, and a point. The 3D data cube is a cube with three intersecting 2D cross tabs.
Madhavi Gundavarapu
Data Cube and OLAP Server

14. Data Cube and OLAP Server
CUBE : The Idea
0-dimensional Aggregate (sum(), max(),...)
a1, a2, ...., aN, f()
Super-aggregate over 1-Dimensional sub-cubes
ALL, a2, ...., aN , f()
a1, ALL, a3, ...., aN , f()
...
a1, a2, ...., ALL, f()
Super-aggregate over 2-Dimensional sub-cubes
ALL, ALL, a3, ...., aN , f()
a1, a2 ,...., ALL, ALL, f()
Madhavi Gundavarapu
Data Cube and OLAP Server

15. Data Cube and OLAP Server
An Example
SELECT model, year, color, sum(sales) as sales
FROM sales
WHERE model in (‘Chevy’)
AND year BETWEEN 1990 AND 1992
GROUP BY CUBE (model, year, color);
Madhavi Gundavarapu
Data Cube and OLAP Server

16. Data Cube and OLAP Server
CUBE Contd.
SELECT model, year, color, sum(sales) as sales
FROM sales
WHERE model in (‘Chevy’)
AND year BETWEEN 1990 AND 1992
GROUP BY CUBE (model, year, color);
Computes union of 8 different groupings:
{(model, year, color), (model, year), (model, color), (year, color), (model), (year), (color), ()}
Madhavi Gundavarapu
Data Cube and OLAP Server

17. Data Cube and OLAP Server
Example Contd.
CUBE
Madhavi Gundavarapu
Data Cube and OLAP Server

18. Data Cube and OLAP Server
GROUPING Function
SQL:1999 uses NULL to represent both ALL and regular null values
GROUPING function
Can be applied to an attribute
Returns 1 if NULL value represents ALL
Returns 0 in all other cases
Madhavi Gundavarapu
Data Cube and OLAP Server

19. Data Cube and OLAP Server
GROUPING Example
SELECT model, year, color, sum(sales) as sales,
GROUPING(model) as model_flag,
GROUPING(year) as year_flag,
GROUPING(color) as color_flag
FROM sales
WHERE model in (‘Chevy’)
AND year BETWEEN 1990 AND 1992
GROUP BY CUBE (model, year, color);
Madhavi Gundavarapu
Data Cube and OLAP Server

20. Data Cube and OLAP Server
Rollup and Drill down
Allow analysts to view data at any desired level of granularity
Rollup
Operation of moving from finer-granularity of data to a coarser granularity
Drill Down
Operation of moving from coarser-granularity of data to a finer granularity
Cannot be generated from coarse-granularity data
Has to be computed from original data
Madhavi Gundavarapu
Data Cube and OLAP Server

21. Data Cube and OLAP Server
ROLLUP Operator
Rollup example
SELECT model, year, color, sum(sales) as sales
FROM sales
WHERE model in (‘Chevy’)
AND year BETWEEN 1990 AND 1992
GROUP BY ROLLUP (model, year, color);
Only 4 groupings are generated
{(model, year, color), (model, year), (model), ()}
Madhavi Gundavarapu
Data Cube and OLAP Server

22. Data Cube and OLAP Server
Summary
SQL-92 has limited functionality to support OLAP operations
SQL:1999 has introduced extensions to address these limitations
provides operators such as CUBE, GROUPING and ROLLUP
Madhavi Gundavarapu
Data Cube and OLAP Server

23. Data Cube and OLAP Server
Questions
Madhavi Gundavarapu
Data Cube and OLAP Server