System Metrics Collectors

System Metrics Collectors

The need to monitor and control the system performances is not new. What is new is the trend of clever, lightweight, easy to setup, open source metric collectors in the market, along with timeseries databases to store these metrics, and user friendly front ends through which to display and analyse the data.

In this post I will compare Telegraf, Collectl and Topbeat as lightweight metric collectors. All of them do a great job of collecting variety (more...)

Connecting Oracle Data Visualization Desktop to OBIEE

Connecting Oracle Data Visualization Desktop to OBIEE

Recently at Rittman Mead we have been asked a lot of questions surrounding Oracle’s new Data Visualization Desktop tool and how it integrates with OBIEE. Rather than referring people to the Oracle docs on DVD, I decided to share with you my experience connecting to an OBIEE 12c instance and take you through some of the things I learned through the process.

In a previous blog, I went though database connections with Data Visualization (more...)

Using R with Jupyter Notebooks and Oracle Big Data Discovery

Using R with Jupyter Notebooks and Oracle Big Data Discovery

Oracle's Big Data Discovery encompasses a good amount of exploration, transformation, and visualisation capabilities for datasets residing in your organisation’s data reservoir. Even with this though, there may come a time when your data scientists want to unleash their R magic on those same datasets. Perhaps the data domain expert has used BDD to enrich and cleanse the data, and now it's ready for some statistical analysis? Maybe you'd like to use R's excellent forecast (more...)

Using SparkSQL and Pandas to Import Data into Hive and Big Data Discovery

Using SparkSQL and Pandas to Import Data into Hive and Big Data Discovery

Big Data Discovery (BDD) is a great tool for exploring, transforming, and visualising data stored in your organisation’s Data Reservoir. I presented a workshop on it at a recent conference, and got an interesting question from the audience that I thought I’d explore further here. Currently the primary route for getting data into BDD requires that it be (i) in HDFS and (ii) have a Hive table defined on top of it. From there, (more...)

Creating ggplot2 graphics using SQL

Did you read the title of this blog post! Read it again.

Yes, Yes, I know what you are saying, "SQL cannot produce graphics or charts and particularly not ggplot2 graphics".

You are correct to a certain extent. SQL is rubbish a creating graphics (and I'm being polite).

But with Oracle R Enterprise you can now produce graphics on your data using the embedded R execution feature of Oracle R Enterprise using SQL. In this (more...)

Privacy – InMobi Pays $1M In Penalties



image credit: WDnet Agency, pexels.com
In 2015 I had written a series of articles on the e-commerce battle between Flipkart and Amazon, one of which focused on why companies are so obsessed with apps Mobile Apps: There’s Something (Profitable) About Your Privacy.
Now it turns out that InMobi has agreed to pay a US$950,000 in civil penalties to "settle charges it violated federal law." InMobi is described by the US Federal Trade (more...)

Cluster Distance using SQL with Oracle Data Mining – Part 4

This is the fourth and last blog post in a series that looks at how you can examine the details of predicted clusters using Oracle Data Mining. In the previous blog posts I looked at how to use CLUSER_ID, CLUSTER_PROBABILITY and CLUSTER_SET.

In this blog post we will look at CLUSTER_DISTANCE. We can use the function to determine how close a record is to the centroid of the cluster. Perhaps we can use this to (more...)

googleVis R package for creating google charts in R

I've recently come across the 'googleVis' R package. This allows you to create a variety of different (typical and standard) charts in R but with the look and feel of the charts we can get from a number of different Google sites.

I won't bore you with some examples in the post but I'll point you to a good tutorial on the various charts.

Here is the link to the mini-tutorial.

Before you can use (more...)

Cloud Allergy – Clouds Security and Changing Notion

| Jun 29, 2016

With my recent role as CTO/Advisor with www.analytos.com, during most of my conversation with Analytics leaders within the company, all are concern over security. At a recent conversation with another entrepreneur friend, one of his solution was stalled due to SQL injection issue on the cloud ( a valid concern , but is it valid ?) .

During my recent startup sting, cloud Allergy word was coined, and it did make sense, because allergies do exist and (more...)

Cluster Sets using SQL with Oracle Data Mining – Part 3

This is the third blog post on my series on examining the Clusters that were predicted by an Oracle Data Mining model. Check out the previous blog posts.

In the previous posts we were able to list the predicted cluster for each record in our data set. This is the cluster that the records belonged (more...)

Rittman Mead at KScope16

Rittman Mead at KScope16

June is the perfect month: summer begins, major football (and futbol) tournaments are in full swing, and of course, KScope16 is on! Rittman Mead have participated in many of the past KScope conferences and will continue that tradition this year with a wide range of presentation and training topics across the Business Intelligence, Data Warehousing, Big Data, and Advanced Analytics subject areas. This year the event is held in Chicago at the Sheraton Grand Chicago, a (more...)

Oracle Business Analytics from a different angle

Gartner’s latest version of the Magic Quadrant for Business Intelligence and Analytics Platforms (#BIAMQ) caused a lot of noise in the Analytics Market. Gartner and Oracle have different views of this market. Gartner sees a difference; “…between a modern BI and Analytics Platform and a traditional, IT-centric Reporting and Analysis Platform”. It’s clear that Oracle and Gartner have a…Read more Oracle Business Analytics from a different angle

Cluster Details with Oracle Data Mining – Part 2

This is the second blog post of my series on examining the clusters that are predicted for by an Oracle Data Mining model for your data. In my previous blog post I should you how to use CLUSTER_ID and CLUSTER_PROBABILITY functions. These are the core of what you will be used when working with clusters and automating the process.

In this blog post I will look at what details are used by the clustering (more...)

Using Jupyter Notebooks with Big Data Discovery 1.2

Using Jupyter Notebooks with Big Data Discovery 1.2

New in Big Data Discovery 1.2 is the addition of BDD Shell, an integration point with Python. This exposes the datasets and BDD functionality in a Python and PySpark environment, opening up huge possibilities for advanced data science work on BDD datasets. With the ability to push back to Hive and thus BDD data modified in this environment, this is important functionality that will make BDD even more useful for navigating and exploring (more...)

Examining predicted Clusters and Cluster details using SQL

In a previous blog post I gave some details of how you can examine some of the details behind a prediction made using a classification model. This seemed to spark a lot of interest. But before I come back to looking at classification prediction details and other information, this blog post is the first in a 4 part blog post on examining the details of Clusters, as identified by a cluster model created using Oracle (more...)

BIWA SIG Bijeenkomst op donderdag 26 mei 2016

Donderdag 26 mei 2016 was er een BIWA SIG Bijeenkomst van de OGh. De onderstaande onderwerpen zijn behandeld: Metadata Management met Oracle Enterprise Metadata Management (OEMM). Eric van Ettekoven van Oracle gaf ons een introductie van deze tool waarmee zowel Data Lineage als Impact Analyse van Informatie systemen een stuk eenvoudiger wordt. De presentatie van…Read more BIWA SIG Bijeenkomst op donderdag 26 mei 2016

Announcing the Dodeca Spreadsheet Management System, Version 7 and the Dodeca Excel Add-In for Essbase

After 18 months of hard work, Applied OLAP is proud to announce the general availability of the Dodeca Spreadsheet Management System, version 7, and the all-new Dodeca Excel Add-In for Essbase.

The Dodeca Spreadsheet Management System provides customers the ability to automate spreadsheet functionality, reducing the risk of spreadsheet errors while increasing productivity.  It combines unprecedented ease-of-use for business users using spreadsheets for planning, budgeting, forecasting, reporting and analysis tasks.  It also provides a robust, (more...)

PREDICTION_DETAILS function in Oracle

When building predictive models the data scientist can spend a large amount of time examining the models produced and how they work and perform on their hold out sample data sets. They do this to understand is the model gives a good general representation of the data and can identify/predict many different scenarios. When the "best" model has been selected then this is typically deployed is some sort of reporting environment, where a list is (more...)

Advanced Analytics in Oracle Data Visualization Desktop

Oracle Data Visualisation Desktop has the feature of being able to include some advanced analytics. In a previous blog post I showed you how to go about installing Oracle R Distribution on your desktop/client machine. This will allow you to make use of some of the advanced analytics features of Oracle Data Visualization Desktop.

The best way to get started with using the advanced analytics features of Oracle Data Visualization Desktop, is to ignore that (more...)

Oracle Data Visualisation Desktop : Enabling Advanced Analytics (R)

Oracle Data Visualization comes with all the typical features you have with Visual Analyzer that is part of BICS, DVCS and OBIEE.

An additional install you may want to do is to install the R language for Oracle Data Visualization Desktop. This is required to enable the Advanced Analytics feature of the tool.

NewImage

After installing Data Visualisation Desktop when you open the Advanced Analytics section and try to add one of the Advanced Analytics graphing (more...)