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Previously, I wrote about the two-tiered data lakehouse with an analytical sandbox and a curated data warehouse in the second layer – the one for productised BI and the other for data science work. I was therefore intrigued when coming across a Forbes article titled ‘Three Keys to a Harmonious Relationship between Data Science and …
As you may have gathered from my previous post, I have become very interested in cloud-based data lakehouses. It was therefore with a keen interest that I read the article ‘Five Effective Ways to Build a Robust Data Lake Architecture’ on Enterprise Talk. While initially I was hoping that the author was going to review …
Seeing as I’m currently working at large for a federated organisation with significantly different and siloed business streams that are managed through a plethora of different systems – ranging from 30-year-old mainframes to modern in-cloud platforms – the topic of data fabrics is very interesting to me. Even more so given how I’m coming from …
Today, the concept of having a data ecosystem in place to improve personalised customer engagements and support customer retention should not be a foreign one. And yet, many companies still struggle to understand how to practically do so. With data providing significant benefits to create such a business advantage, it has become critical to understand …
In previous posts I covered the data lake, approaches to “building” the lake and the data lake’s relationship with the traditional data warehouse. However as rosy as all that may seem, there are some people quite opposed to using the data lake as an all-encompassing free-for-all at-scale staging area. To an extent, I tend to …
In a previous post I gave a high level description and overview of the data lake. Informally speaking, from a BI point of view, a data lake is a large scaled-out all-encompassing free-for-all unstructured data staging area. In this post I take the discussion further to investigate whether it replaces or interacts with the data …
In this post, I’m looking at approaches to lift BI up from a mere enabling IT function to an enterprise strategic business function. This is an elaboration on discussions that were recorded in TDWI’s BI Journal, Vol 18 No 4 (http://tdwi.org/research/2013/12/business-intelligence-journal-vol-18-no-4.aspx), around aligning BI with business strategy. I have previously also published a post on …
The Big Data movement is transforming long-established data warehouse architectures into multifaceted analytical ecosystems, in which the time dimension has also seen been ratcheted up a few notches. In the good old days data was extracted from operational systems, batch-processed through a data warehouse, transformed to information and delivered to a relatively small group of …
I have just returned from attending the 5th Annual Big Data Warehousing & Business Intelligence Summit, organised by Enterprise IQ, held in Sydney on 27 – 29 November 2012. I participated in two panel sessions, firstly as a panelist on doing business in the Big Data age, and secondly moderating the session on the architectures …
The success of every decision is closely related to the quality of the information that was used to make that decision. For this reason, Data Quality is very closely related to Business Intelligence. Data quality checks and active data quality controls should be embedded into the loading and reporting processes. This can ensure the quality …
