Month: April 2016

Oracle Data Visualisation : Setting up a Connection to your DB

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Using Oracle Data Visualisation is just the same or very similar as to using the Cloud version of the tool.

In this blog post I will walk you through the steps you need to perform the first time you use the Oracle Data Visualization client tool and to quickly create some visualizations.

Step 1 – Create a Connection to your Oracle DB and Schema

After opening Oracle Data Visualisation client tool client on the Data Sources icon that is displayed along the top of the screen.

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Then click on the ‘Connection’ button. You need to create a connection to your schema in the Oracle Database. Other options exist to create a connection to files etc. But for this example click on ‘From Database.

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Enter you connections details for your schema in your Oracle Database. This is exactly the same kind of information that you would enter for creating a SQL Developer connection. Then click the Save button.

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Step 2 – Defining the data source for your analytics

You need to select the tables or views that you are going to use to build up your data visualizations. In the Data Sources section of the tool (see the first image above) click on the ‘Create Data New Data Source’ button and then select ‘From Database’. The following window (or one like it) will be displayed. This will contain all the schemas in the DB that you have some privileges for. You may just see your schema or others.

Select your schema from the list. The window will be updated to display the tables and views in the schema. You can change the layout from icon based to being a list. You can also define a query that contains the data you want to analyse using the SQL tab.

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When you have select the table or view to use or have defined the SQL for the data set, a window will be displayed showing you a sample of the data. You can use this window to quickly perform a visual inspection of the data to make sure it is the data you want to use.

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The data source you have defined will now be listed data sources part of the tool. You can click on the option icon (3 vertical dots) on the right hand side of the data source and then select Create VA Project from the pop up menu.

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Step 3 – Create your Oracle Data Visualization project

When the Visual Analyser part of the tool opens, you can click and drag the columns from your data set on to the workspace. The data will be automatically formatted and displayed on the screen. You can also quickly generate lots of graphics and again click and drag the columns on the graphics to define various element.

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Oracle Data Visualization Desktop – now available

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After a bit of a long wait Oracle have finally release Oracle Data Visualization for the desktop. The desktop version of this tool is only available for Windows desktops at the moment. I’m sure Oracle will be bringing out versions of other OS soon (I hope).

To get you hands on the Oracle Data Visualization to to the following OTN webpage (click on this image)

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After downloading has finished, you can run the installer.

When the Oracle Installer opens you will be prompted to enter the required details or to accept the defaults, as outlined below.

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  • Installation Location : Decide where you are going to have the Oracle Data Visualization tool installed on your desktop. The default location is C:\Program Files\Oracle Data Visualization Desktop . Click Next
  • Options : There are 2 check boxes for ‘Create desktop shortcut’ and ‘Deploy samples’. Leave both of these checked, as you will probably want these. Click Next.
  • Summary : Lists a summary of the installation. There is nothing really for you to do here, so on the Install button.
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  • Progress : You can ten sit back and monitor the progress of the installation. The installation tool about 4 minutes on my small Windows VM
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When the installation is complete you can now fire up Oracle Data Visualization and enjoy. If you have just installed the tool it will automatically be started for you.

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When the tool has finished all the configurations that it needs to do, the tool will open with the following window and shows a sample projects for you to get an idea of some of the things that are possible.

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For more details on the tool and on the Oracle Cloud hosted version click on the following image to get to the Oracle webpage for the product.

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Accessing the R datasets in ORE and SQL

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When you install R you also get a set of pre-compiled datasets. These are great for trying out many of the features that are available with R and all the new packages that are being produced on an almost daily basis.

The exact list of data sets available will depend on the version of R that you are using.

To get the list of available data sets in R you can run the following.

> library(help="datasets")

This command will list all the data sets that you can reference and start using immediately.

I’m currently running the latest version of Oracle R Distribution version 3.2. See the listing at the end of this blog post for the available data sets.

But are these data sets available to you if you are using Oracle R Enterprise (ORE)? The answer is Yes of course they are.

But are these accessible on the Oracle Database server? Yes they are, as you have R installed there and you can use ORE to access and use the data sets.

But how? how can I list what is on the Oracle Database server using R? Simple use the following ORE code to run an embedded R execution function using the ORE R API.

What? What does that mean? Using the R on your client machine, you can use ORE to send some R code to the Oracle Database server. The R code will be run on the Oracle Database server and the results will be returned to the client. The results contain the results from the server. Try the following code.

ore.doEval(function() library(help="datasets")) 

# let us create a functions for this code
myFn <- function() {library(help="datasets")}

# Now send this function to the DB server and run it there.
ore.doEval(myFn)

# create an R script in the Oracle Database that contains our R code
ore.scriptDrop("inDB_R_DemoData")
ore.scriptCreate("inDB_R_DemoData", myFn)
# Now run the R script, stored in the Oracle Database, on the Database server
#   and return the results to my client
ore.doEval(FUN.NAME="inDB_R_DemoData")

Simple, Right!

Yes it is. You have shown us how to do this in R using the ORE package. But what if I’m a SQL developer. Can I do this in SQL? Yes you can. Connect you your schema using SQL Developer/SQL*Plus/SQLcl or whatever tool you will be using to run SQL. Then run the following SQL.

select * 
from table(rqEval(null, 'XML', 'inDB_R_DemoData'));

This SQL code will return the results in XML format. You can parse this to extract and display the results and when you do you will get something like the following listing, which is exactly the same that is produced when you run the R code that I gave above.

So what this means is that evening if you have an empty schema with no data in it, and as long as you have the privileges to run embedded R execution, you actually have access to all these different data sets. You can use these to try our R using the ORE SQL APIs too.

		Information on package ‘datasets’

Description:

Package:       datasets
Version:       3.2.0
Priority:      base
Title:         The R Datasets Package
Author:        R Core Team and contributors worldwide
Maintainer:    R Core Team 
Description:   Base R datasets.
License:       Part of R 3.2.0
Built:         R 3.2.0; ; 2015-08-07 02:20:26 UTC; windows

Index:

AirPassengers           Monthly Airline Passenger Numbers 1949-1960
BJsales                 Sales Data with Leading Indicator
BOD                     Biochemical Oxygen Demand
CO2                     Carbon Dioxide Uptake in Grass Plants
ChickWeight             Weight versus age of chicks on different diets
DNase                   Elisa assay of DNase
EuStockMarkets          Daily Closing Prices of Major European Stock
                        Indices, 1991-1998
Formaldehyde            Determination of Formaldehyde
HairEyeColor            Hair and Eye Color of Statistics Students
Harman23.cor            Harman Example 2.3
Harman74.cor            Harman Example 7.4
Indometh                Pharmacokinetics of Indomethacin
InsectSprays            Effectiveness of Insect Sprays
JohnsonJohnson          Quarterly Earnings per Johnson & Johnson Share
LakeHuron               Level of Lake Huron 1875-1972
LifeCycleSavings        Intercountry Life-Cycle Savings Data
Loblolly                Growth of Loblolly pine trees
Nile                    Flow of the River Nile
Orange                  Growth of Orange Trees
OrchardSprays           Potency of Orchard Sprays
PlantGrowth             Results from an Experiment on Plant Growth
Puromycin               Reaction Velocity of an Enzymatic Reaction
Theoph                  Pharmacokinetics of Theophylline
Titanic                 Survival of passengers on the Titanic
ToothGrowth             The Effect of Vitamin C on Tooth Growth in
                        Guinea Pigs
UCBAdmissions           Student Admissions at UC Berkeley
UKDriverDeaths          Road Casualties in Great Britain 1969-84
UKLungDeaths            Monthly Deaths from Lung Diseases in the UK
UKgas                   UK Quarterly Gas Consumption
USAccDeaths             Accidental Deaths in the US 1973-1978
USArrests               Violent Crime Rates by US State
USJudgeRatings          Lawyers' Ratings of State Judges in the US
                        Superior Court
USPersonalExpenditure   Personal Expenditure Data
VADeaths                Death Rates in Virginia (1940)
WWWusage                Internet Usage per Minute
WorldPhones             The World's Telephones
ability.cov             Ability and Intelligence Tests
airmiles                Passenger Miles on Commercial US Airlines,
                        1937-1960
airquality              New York Air Quality Measurements
anscombe                Anscombe's Quartet of 'Identical' Simple Linear
                        Regressions
attenu                  The Joyner-Boore Attenuation Data
attitude                The Chatterjee-Price Attitude Data
austres                 Quarterly Time Series of the Number of
                        Australian Residents
beavers                 Body Temperature Series of Two Beavers
cars                    Speed and Stopping Distances of Cars
chickwts                Chicken Weights by Feed Type
co2                     Mauna Loa Atmospheric CO2 Concentration
crimtab                 Student's 3000 Criminals Data
datasets-package        The R Datasets Package
discoveries             Yearly Numbers of Important Discoveries
esoph                   Smoking, Alcohol and (O)esophageal Cancer
euro                    Conversion Rates of Euro Currencies
eurodist                Distances Between European Cities and Between
                        US Cities
faithful                Old Faithful Geyser Data
freeny                  Freeny's Revenue Data
infert                  Infertility after Spontaneous and Induced
                        Abortion
iris                    Edgar Anderson's Iris Data
islands                 Areas of the World's Major Landmasses
lh                      Luteinizing Hormone in Blood Samples
longley                 Longley's Economic Regression Data
lynx                    Annual Canadian Lynx trappings 1821-1934
morley                  Michelson Speed of Light Data
mtcars                  Motor Trend Car Road Tests
nhtemp                  Average Yearly Temperatures in New Haven
nottem                  Average Monthly Temperatures at Nottingham,
                        1920-1939
npk                     Classical N, P, K Factorial Experiment
occupationalStatus      Occupational Status of Fathers and their Sons
precip                  Annual Precipitation in US Cities
presidents              Quarterly Approval Ratings of US Presidents
pressure                Vapor Pressure of Mercury as a Function of
                        Temperature
quakes                  Locations of Earthquakes off Fiji
randu                   Random Numbers from Congruential Generator
                        RANDU
rivers                  Lengths of Major North American Rivers
rock                    Measurements on Petroleum Rock Samples
sleep                   Student's Sleep Data
stackloss               Brownlee's Stack Loss Plant Data
state                   US State Facts and Figures
sunspot.month           Monthly Sunspot Data, from 1749 to "Present"
sunspot.year            Yearly Sunspot Data, 1700-1988
sunspots                Monthly Sunspot Numbers, 1749-1983
swiss                   Swiss Fertility and Socioeconomic Indicators
                        (1888) Data
treering                Yearly Treering Data, -6000-1979
trees                   Girth, Height and Volume for Black Cherry Trees
uspop                   Populations Recorded by the US Census
volcano                 Topographic Information on Auckland's Maunga
                        Whau Volcano
warpbreaks              The Number of Breaks in Yarn during Weaving
women                   Average Heights and Weights for American Women

DAMA Ireland: Data Protection Event 5th May

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We have our next DAMA Ireland event/meeting coming up on the 5th May, and will be in our usual venue of Bank of Ireland, 1 Grand Canal Dock.

Our meeting will cover two topics. The main topic for the evening will be on Data Protection. We have Daragh O’Brien (MD of Castlebridge Associate) presenting on this. Daragh is also the Global Data Privacy Officer for DAMA International. He has also been invoked in contributing to the next version of the DMBOK, that is coming out very soon.

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We also have Katherine O’Keefe who will be talking the DAMA Certified Data Management Practitioners (CDMP) certification. Katherine has been working with DAMA International on updates to the new CDMP certification.

To check out more details of the event/meeting, click on the Eventbrite image below. This will take you to the event/meeting details and where you can also register for the meeting.

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Cost : FREE

When : 5th May

Where : Bank of Ireland, 1 Grand Canal Dock

PS: Please register in advance of the meeting, as we would like to know who and how many are coming, to allow us to make any necessary arrangements.

Oracle Advanced Analytics in the Oracle Cloud

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You have heard about the cloud? Right? Even the Oracle Cloud?

If you haven’t, then maybe we need to look at how you can learn more about the Oracle Cloud.

Over the past while, and in the past few weeks in particular, Oracle has been advertising about how you can get a trail Oracle cloud service setup for FREE. Well it is free for one month when you set it up on the Oracle website (cloud.oracle.com).

As I like to talk about and use the Oracle Advanced Analytics (OAA) option (a lot), I thought I’d just give you some pointers on how to use OAA on the Oracle cloud.

To do this you need to set up an account on the Oracle cloud website (your Oracle single sign on should help with making that process a lot quicker). There are lots of websites and blog that will talk/show you through the process. Then you need to select what Database as a Service that you want to setup

OAA is not available on the Database Schema Service just yet (maybe one day they will)

Although Oracle Advanced Analytics comes pre-installed in the Oracle Enterprise Edition database (yes it is a separately priced option) when you install it on your own servers, but for the Enterprise Edition DaaS OAA is not part of it.

DaaS has the following versions

  • Standard Edition Service 
  • Enterprise Edition Service 
  • High Performance Service 
  • Extreme Performance Service

OAA is only available for these last two versions of the DaaS.

High Performance DaaS: Multitenant, Partitioning, Real Application Testing, Advanced Compression, Advanced Security, Label Security, Database Vault, OLAP, Advanced Analytics, Spatial and Graph, Diagnostics Pack, Tuning Pack, Database Lifecycle Management Pack, Data Masking & Subsetting Pack and Cloud Management Pack for Oracle Database.

Extreme Performance DaaS: In-Memory Database, RAC (Real Application Clusters), Active Data Guard, Multitenant, Partitioning, Real Application Testing, Advanced Compression, Advanced Security, Label Security, Database Vault, OLAP, Advanced Analytics, Spatial and Graph, Diagnostics Pack, Tuning Pack, Database Lifecycle Management Pack, Data Masking & Subsetting Pack and Cloud Management Pack for Oracle Database.

Oracle Advanced Analytics has two main products or components. The first is the in-database Oracle Data Mining features. This are part of the High Performance and Extreme Performance DaaS offerings. But Oracle R Enterprise is not installed on these DaaS. Well if kind of is if you can get an 11g DaaS, but at time of writing this post ORE is not part of the 12c DaaS images. So you will need to factor in some time to go and install ORE, if you need to use it.

I’ve been lucky to have one of these DaaS with OAA trials and with thanks to Thomas Kurian he has extended these trials to 12 months for all Oracle ACE Directors. Thank you Thomas.

When you get your DaaS setup you just need to configure your connection privileges, ssh, etc and away you go. All you need to do is to move your data across the internet to your own Oracle DaaS, and once it is in the DaaS all your OAA and other analytics is performed on the Database Server. Only the results are returned to you and displayed in your tool. This significantly reduces the processing time for your data and removes the need to constantly extract your data (in whole or in parts) to feed into other advanced analytics tools.

So if you haven’t tried Oracle Advanced Analytics yet, then go ahead and setup your free trial of Oracle DaaS and try it out. You never know what you might discover by using Oracle Advanced Analytics (in the cloud)

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