Getting The Users’ Trust – Part 1

Looking back over some of my truly ancient Rittman Mead blogs (so old in fact that they came with me when I joined the company soon after Rittman Mead was launched), I see recurrent themes on why people “do” BI and what makes for successful implementations. After all, why would an organisation wish to invest serious money in a project if it does not give value either in terms of cost reduction or increasing profitability (more...)

Using Oracle GoldenGate for Trickle-Feeding RDBMS Transactions into Hive and HDFS

A few months ago I wrote a post on the blog around using Apache Flume to trickle-feed log data into HDFS and Hive, using the Rittman Mead website as the source for the log entries. Flume is a good technology to use for this type of capture requirement as it captures log entries, HTTP calls, JMS queue entries and other “event” sources easily, has a resilient architecture and integrates well with HDFS and Hive. (more...)

Analyzing Twitter Data using Datasift, MongoDB, Hive and ODI12c

Last week I posted an article on the blog around analysing Twitter data using Datasift, MongoDB and Pig, where I used the Datasift service to stream tweets about Rittman Mead into a MongoDB NoSQL database, and then queried the dataset using Pig. The context for this is the idea of a “data reservoir”, where we supplement the more traditional file and relational datasets we find in data warehouses with other data, typically machine generated, (more...)

Big Data 2.0 and Agile BI all at Irish BI OUG (24 September).

I will give a presentation on 24 September at the Jury’s Inn in Dublin on the next generation of Big Data 2.0 tools and architecture.

Over the last two years there have been significant changes and improvements in the various Big Data frameworks. With the release of Yarn (Hadoop 2.0) the most popular of these platforms now allows you to run mixed workloads. Gone are the days when Hadoop was only good for (more...)

Responding in Real-Time with Big Data By Mala Ramakrishnan

| Aug 4, 2014

For an organization to respond in real-time it needs to acquire or develop systems
that can respond in real-time. Such systems need to be able to rapidly
determine that a response is required and determine also what the
appropriate and relevant response should be – they need to decide when
and how to act. These kinds of decision-making systems are known as
Decision Management Systems. To ensure that a response is delivered in
real-time, more (more…)

Oracle Data Integrator and Hadoop. Is ODI the only ETL tool for Big Data that works?

Both ODI and the Hadoop ecosystem share a common design philosophy. Bring the processing to the data rather than the other way around. Sounds logical, doesn’t it? Why move Terabytes of data around your network if you can process it all in the one place. Why invest millions in additional servers and hardware just to transform and process your data?

In the ODI world this approach is known as ELT. ELT is a marketing concept (more...)

Permissions for both HDFS and local fileSystem paths

| Jul 18, 2014

Hi All,

Permission issues is one of the key error , while setting up Hadoop Cluster, while debugging some error found below table on http://hadoop.apache.org/ . It’s a good scorecard to keep handy.

 

Permissions for both HDFS and local fileSystem paths

The following table lists various paths on HDFS and local filesystems (on all nodes) and recommended permissions:

Filesystem Path User:Group Permissions
local dfs.namenode.name.dir hdfs:hadoop drwx——
local dfs.datanode.data.dir (more...)

War of the Hadoop SQL engines. And the winner is …?

You may have wondered why we were quiet over the last couple of weeks? Well, we locked ourselves into the basement and did some research and a couple of projects and PoCs on Hadoop, Big Data, and distributed processing frameworks in general. We were also looking at Clickstream data and Web Analytics solutions. Over the next couple of weeks we will update our website with our new offerings, products, and services. The article below summarises (more...)

Big Data doom mongers need to look outside of the marketing department

In every change there are hype machines that over play and sages who call doom.  Into the Big Data arena steps David Searls to proclaim that Big Data is a myth and simply hype which is set to burst in an article over at ZDNet. But big data, he said, is nothing more than the myth that collecting vast amounts of data can help companies know customers better than those customers even know

Editor’s Choice award at ODTUG Kscope14: NoSQL and Big Data for the Oracle Professional

My paper on NoSQL and Big Data won the Editor’s Choice award at ODTUG Kscope14. Here are some key points from the paper: The relational camp made serious mistakes that limited the performance and usefulness of the relational model. NoSQL is based on the incorrect premise that tables in the relational model must be mapped to […]

Trying to understand the Oracle Reference Architecture for Information Management

Last month I have been attending the RittmanMead BI Forum 2014. In the wrap-up I mentioned a presentation by Andrew Bond & Stewart Bryson. They had a very nice presentation about the Oracle Information Management Reference Architecture. This needed some further investigation from my part. This blogpost is a first summary of the information I found online so far. There is […]

Hadoop for Oracle Professionals Article on Oracle Scene

Oracle Scene (the publication of United Kingdom Oracle Users Group) has published my article "Hadoop for Oracle Professionals", where I have attempted, like many others, to demystify the terms such as Hadoop, Map/Reduce and Flume. If you were interested in Big Data and what all comes with understanding it, you might find it useful.

A PDF version of the article can be downloaded here http://www.proligence.com/art/oracle_scene_summ14_hadoop.pdf

MDM isn’t about data quality its about collaboration

I'm going to state a sacrilegious position for a moment: the quality of data isn't a primary goal in Master Data Management Now before the perfectly correct 'Garbage In, Garbage Out' statement let me explain.  Data Quality is certainly something that MDM can help with but its not actually the primary aim of MDM. MDM is about enabling collaboration, collaboration is about the cross-reference

Lipstick on the iceberg – why the local view matters for IT evolution

There is a massive amount of IT hype that is focused on what people see, its about the agile delivery of interfaces, about reporting, visualisation and interactional models.  If you could weight hype then it is quite clear that 95% of all IT is about this area.  Its why we need development teams working hand-in-hand with the business, its why animations and visualisation are massively important.

How to select a Hadoop distro – stop thinking about Hadoop

Scoop, Flume, PIG, Zookeeper.  Do these mean anything to you?  If they do then the odds are you are looking at Hadoop.  The thing is that while that was cool a few years ago it really is time to face it that HDFS is a commodity, Map Reduce is interesting but not feasible for most users and the real question is how we turn all that raw data in HDFS into something we can actually (more...)

Need for Defining Reference Architecture For Big Data

Hi Fellow Big Data Admirers ,

With big data and analytics playing an influential role helping organizations achieve a competitive advantage, IT managers are advised not to deploy big data in silos but instead to take a holistic approach toward it and define a base reference architecture even before contemplating positioning the necessary tools. 

My latest print media article (5th in the series) for CIO magazine (ITNEXT) talks extensively about need of reference architecture in (more...)

Data Lakes will replace EDWs – a prediction

Over the last few years there has been a trend of increased spending on BI, and that trend isn't going away.  The analyst predictions however have, understandably, been based on the mentality that the choice was between a traditional EDW/DW model or Hadoop.  With the new 'Business Data Lake' type of hybrid approach its pretty clear that the shift is underway for all vendors to have a hybrid

How to find out a table type in Hive Metastore.

| Apr 10, 2014

Hi All

As Hive metastore is getting into the center of nervous system for the different type of  SQL engines like Shark and Impala. It getting equally difficult to distinguish type of table created in Hive metastore. Eg. if we create a impala table using impala shell you will see the same table on hive prompt and vice versa. See the below example

 

Step 1 : “Create Table” in Impala Shell and “Show Table” (more...)

How To Create External Hive Table on HBase

| Mar 28, 2014

Hi All,

While building a data flow for replacing one of the EDW’ workflow using Big Data technology stack , came across some interesting findings and issues.  Due to  UPSERT ( INSERT new records or UPDATE existing records depending) nature of data we had to use Hbase, but to expose the outbound feed we need to do some calculation on HBase and publish that to Hive as external. Even though conceptually , its easy to create an (more...)

Hbase : Co-relation between RegionServer and Region

| Mar 20, 2014

Hi All

While looking into HBase performance issue, one of the suggestion was to have more region for a larger table. There was some confusion around, “Region” vs “RegionServer” . While doing some digging, found a simple text written below.

The basic unit of scalability and load balancing in HBase is called a region. Regions are essentially contiguous ranges of rows stored together. They are dynamically split by the system when they become too large. Alternatively, they may (more...)