SQL

data variety / shutterstock

Data variety stands out from the three Vs of big data from the report of the big data survey conducted by NewVantage Partners in 2012. One of the survey results shows companies focusing more on data variety instead of data volume both now and in the next three years.[read more]

SaaS / shutterstock

Data stored in SaaS applications is often inaccessible to BI tools. This is a major headache to early adopters of SaaS applications. With on-premise applications, IT departments can bypass the application and access data directly from the underlying database.[read more]

Big Data Analytics

We are reaching a crossroads in the world of analytics. Over the years, we have seen analytic environments and data environments begin to merge through the advent of in-database processing within relational database engines. But is this causing a case of "2 steps forward, 4 steps back"?[read more]

Spreadsheets and BI / shutterstock

The year of 2012 witnessed a sharp and substantial increase of BI. Unexpectedly, the spreadsheet turns out to be the one developed and welcomed most, instead of other more sophisticated BI tools like SAP BusinessObjects or Qlikview. Why is the spreadsheet still ruling the BI world?[read more]

Big data gaming

Online game developer Zynga operates at such a large scale that on a regular day, Zynga delivers one petabyte of content. They have built a flexible cloud server center that can easily add up to 1,000 servers in just 24 hours. So, big data is truly big at Zynga, but how do they cope with it?[read more]

Business Intelligence

How do you assess the overall health and maturity of your Business Intelligence Initiative? This article is the first in a series that reviews the topics to be considered when reviewing the current status of a traditional Business Intelligence initiative.[read more]

SQL is a database query and programming language for retrieving, updating, and managing the data from relational database. Nowadays, SQL is a basic requirement for every programmer. However, there's a disadvantage: SQL is especially designed for technical personnel.[read more]

The whole idea behind business intelligence is to try to make something meaningful out of the gigantic tables of data, in order to reach, ultimately, a number of informed decisions based on that data. Hoping, of course, that those decisions will have the expected impact.[read more]

It seems that there might sometimes be a clash between “analytics” and “social.” For example, today’s airlines have great analytics, and they seem to have concluded that, for whatever reason, people generally prefer low prices instead of a pleasurable flight. After all, it IS possible to have a wonderful flying experience: just travel in first class, or jump in a private jet.[read more]

IT/shutterstock.com

For some time now, I've been taking an interest in NoSQL because of its positioning in the Big Data space. I've always had a real problem with the term - whether it means Not SQL or Not Only SQL - because defining anything by what it's not is logical nonsense.[read more]

sales metrics/shutterstock.com

Sales performance isn’t just about sales numbers and sales activities. Sure, trends in sales success are deeply tied to sales information, but many other actions support the impact of your sales team: from prospect behavior in the marketing funnel to sales development performance to the processes applied in the company’s financial and customer support practices.[read more]

Wikipedia image

Although the current OLAP tools are splendid regarding its look and feel, few on-line analysis capabilities powerful enough are provided actually. Then, what kind of OLAP do we need? What kind of OLAP tools we need?[read more]

The need to extract and store data from Hadoop into other database systems and thereby lose the computing power of Hadoop has been the Achilles heel of this big data technology. Analysts who want interactive and iterative discovery of their data now do not have to depend on the Hadoop Hive query language interface and can use more familiar tools like MicroStrategy and Tableau for analytics.[read more]

Andreas Meyer/shutterstock.com

Tackling machine data for an 800M+ record database.[read more]

...whatever the rationale, the association of BI and SQL is deeply embedded in the minds of most practitioners. So, the question arises--what about NoSQL; how does this relate to BI? Can it be of use in data warehousing?[read more]