Business Intelligence Barista: Mixing your choice of BI Coffee with Tableau, Power BI or Qlikview?

Business Intelligence Barista: Mixing your choice of BI Coffee with Tableau, Power BI or Qlikview?

Choosing a Business Intelligence is a bit like making coffee for the whole company. Everybody likes it their way, and they want it right now. Plus, everybody wants it differently. So, given that everyone has different requirements, how do you go about keeping everybody happy? If you think about how hard it is to keep everyone happy when you’re just making coffee, think how hard it is to select a business Intelligence solution. Not just any solution…. the *right* solution. 

So, given that everyone has different requirements, how do you go about keeping everybody happy? If you think about how hard it is to keep everyone happy when you’re just making coffee, think how hard it is to select a business Intelligence solution. Not just any solution…. the *right* solution. The one that will keep everyone happy and give them what they want. The solution that will keep the ambulance away from the door, where constraints must be met or there will be serious trouble. The solution that will keep everyone out of danger whilst making sure that the sprinkle lovers get their sprinkles, and the folks who like a chocolate covered spoon in their coffee get a little chocolate covered spoon – in milk, dark or white…

Hopefully this article could provide an insight for you to decide the best BI tools for you company. If you would like to know further, or if you have any question, please contact us or leave us comments below.

2013 in review: Big data, bigger expectations?

In the parlance of the industry, big data’s feat was a result of the successful convergence of the “three Vs”:

Volume: A large amount of data

Variety: A wide range of data types and sources

Velocity: The speed of data moving from its sources, into the hands of those who need it

Although other Vs have since been contemplated, such as Veracity and Value, the original three attributes promised big data could go far beyond the boundaries of traditional databases, which require data to be stored in rigid rows and columns.

However, over the past year, reality began to sink in: People came to realize what big data could and could not do. Unfortunately, performing large-scale analytics in real time proved to be more daunting than originally thought. Although Hadoop continues to be the world’s most popular big data processing platform, it was designed for batch processing and is far too slow for real-time use.

Reference: 2013 in review: Big data, bigger expectations?