Bigdatapump has been awarded the Microsoft Gold Partner status with Gold Data Platform competency.
With the democratization of data, open source tools and everyone hiring data scientists, what is left to differentiate on?
One of the most difficult aspects of providing business-relevant analytics is identifying the business problem.
While gathering, refining and analyzing data has become a part of everyday business in all industries, several companies are still figuring out how to best turn that asset into a currency.
BIGDATAPUMP has been awarded the Microsoft Gold Partner status with Gold Data Analytics competency.
Security in computing industry can be said to consist both physical and virtual security. Neither of those are anything to take lightly.
Postponing cloud transformation is like burning the candle at both ends while not taking the time to install a light bulb; eventually you’ll end up in the dark.
The time of the cloud is here. This means the traditional on-premise playbook is no longer valid and it is those who embrace data driven digital transformation that will survive - and prosper.
I've had the privilege to spend the last six months with BIGDATAPUMP's Data Science team in Finland. It's been a great experience to work in a multi-cultural environment with very talented individuals.
Microsoft Build was organized once again a couple of weeks back. Read our thoughts about the event, and how we agree with Microsoft's vision of the future.
BIGDATAPUMP has been awarded the Microsoft Gold Partner status with Cloud Platform competency.
BIGDATAPUMP has now landed in Sweden and is ready to innovate in this new market with new customers. Here are some of my thoughts on how the big data and analytics landscape has changed since we started in 2012 to this day and beyond.
We wanted to study the applicabity of Microsoft Cognitive Services in designing an app that would come up with a set of whisky recommendations based on spoken preferences.
BIGDATAPUMP has been awarded Microsoft Data Analytics competency for continuosly delivering, deploying and supporting Microsoft Business Intelligence and Data Analytics solutions.
Good news continue on Microsoft Azure front! BIGDATAPUMP has now joined the Microsoft's Business Intelligence Partner Program.
SQL Server Reporting Services will have the capability of hosting Power BI reports shortly, but in the meantime I had to find a workaround to execute a Power BI demo on an on-premise environment.
So far, we have succeeded in growing our company substantially year after year, as well as in creating a loyal customer base and a highly committed internal team innovating with us in big data analytics. But how to keep the company on the success path in the future?
BIGDATAPUMP has been awarded Microsoft Silver Cloud Platform competency for continuosly delivering IoT and Data Platform solutions to customers seeking to differentiate their business.
This blog post is intended for readers who already have some experience on building Data Warehouses with earlier versions of SQL Server (2008 or 2012) and are looking for updating their knowledge on how to do it today on SQL Server 2016 and/or on Azure. In addition, I included some insight on the technology trends on the matter.
Couple days ago The Economist published an article titled "Linux and AWS: Cloud chronicles". The article stressed the undeniable importance of Linux and Amazon Web Services (AWS) in the upsurge of cloud computing and went on to explain how network effects have helped both grow in popularity. Despite similar paths, article predicted that their future will diverge and Linux will "happily plod along" whereas "AWS could end up dominating the IT industry just as IBM’s System/360, a family of mainframe computers, did until the 1980s".
Cloud analytics have changed the world big time. BIGDATAPUMP is an independent and objective solution provider using always the best fit technology for each purpose. Personally I have not written earlier about any specific analytics technology but this time I decided to make an exception. Microsoft and Azure deserve a special focus.
tl;dr: Gartner's Magic Quadrant for advanced analytics doesn't do a good job in helping to decide which analytics tool(s) to acquire. It also misses the point that open source projects are the real leaders in advanced analytics. Vendors that position themselves to complement open source projects rather than competing against them will be ones to watch.
Online advertisement is sold more and more through ad exchanges and auctions in particular. Ad auctions are an efficient way of buying and selling ad space and they will get more popular simply because they are better for everyone. In theory, auctions are "strategy proof" and hence you can't game them.
In BIGDATAPUMP, we have had two main BI visualization tool families in most active use in our customer projects: Qlik products and Tableau. However, also Microsoft’s Power BI started to look really promising, and in February it ranked really well in Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms.
Last year Microsoft acquired Revolution Analytics which provided open and enterprise distributions of hugely popular statistical computing language R. Earlier this year, Microsoft launched Microsoft R open and Microsoft R Server which are built upon Revolution Analytics software.
Predictive analytics and machine learning are the hot topics in advanced analytics at the moment, but sometimes predicting how the KPIs on your dashboard look next week isn't enough. You might want to know how they look if you run a new marketing campaign or what is driving the new trend.
BIGDATAPUMP has been operating soon for four years. Over these years, the company has grown from “one man and a laptop” company to an organization employing 25 highly qualified data and analytics professionals and having an enthusiastic and highly loyal customer base.
Many people have a biased view of what econometrics really is and how it can be applied to business problems. In the following posts I will introduce some methods from applied econometrics, structural modelling and panel data/time series tools and show how they can be used to solve problems where standard statistical and machine learning tools do not work.
Many of the Cloud Solutions today are based on the use of Virtual Machines as a part of the Solution. Implementations vary, but as Platform as a Service (PaaS) and Software as a Service (SaaS) offering is growing rapidly, the need for using Virtual Machines for the same purposes, is declining.
A solution implementation architect’s workflow nowadays might look like magic for an outsider. Not only can you ramp up components of your architecture with few clicks of a mouse but you can conjure whole multi-machine-solution infrastructures in a neatly organized, modular, portable and repeatable way.