Tag Archives: Business Intelligence

Abstract data warehousing and Rolls Royces

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When should you use data abstraction in your data warehouse?
(Short answer: when it is profitable for your company)

Cisco has a nice introduction on the best practice of using data abstraction in your Enterprise Data Warehouse (EDW). They argue that the best practice is to transform your data from its original form, into what your business needs are.

From an IT perspective, we often jump on the “Rolls Royce” solution, rather then figuring out what the customer actually needs. We often make pretty and nice looking solutions in scenarios where we might do as well with a quick solution that does the job.

From a business perspective, it is crucial that your deliverables are cost effective and have a short time to market. In other words: the IT solution must make more money then it costs. All in all, do a profitability study / have a positive business case.

Why is this important? Because building a data warehouse is expensive. Building a «Rolls Royce» solution, might be more then you will get funding for. Keep in mind that between 70% and 80% of corporate BI projects fail, according to Gartner. Don’t be too ambitious.

I don’t believe EDW projects are much different. But, of course, there are more reasons a warehouse project fail.

Make sure your BI or EDW project is profitable for your business. Then figure out if you can afford the cost of having a best practice abstract / standardised data warehouse. Don’t implement an expensive solution just because everybody else does it. Look at how this affects time to market for your EDW. How will it affect the time it takes to integrate new data or a new source? (Also, be careful about running large IT projects).

This being said, at some point, most mature EDW initiatives will implement a data abstraction layer into their warehouse.

By the way: i believe the “Rolls Royce” solution is often chosen by IT because it is what most are taught at colleges and universities. Maybe we should introduce a topic «cost effective solutions»?

Should companies depreciate email?

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Todays post is about electronic mail. It occurred to me, that I might be writing to the generation 40+. Everyone from 13-30s think they have it all figured out, especially in regards to computers.

Lots of companies depreciate the use of email. An argument I’ve heard often is: «But, the young generation today doesn’t use email, they use the hippest social media tool around!». Another argument is: «our employees spend too much time reading, sorting and answering mail».

Well, I like email. For me it is all about using the right tool for the job. I won’t use email for collaborating on a document, we have file repositories for that. I wouldn’t use it for marketing, as we have social media for this. On the other hand, email is a very versatile tool. It is widespread, and although it has its flaws, email is used by everyone and every company.

We do spend a lot of time organizing and answering e-mails. In my opinion it is because it has become a part of how we communicate at work. Email will not die for a very long time. The key is knowing when to send a mail, and when not to. Read through your email before you send it (link in norwegian). Lastly, use automated email sorting rules, and sort your inbox. In my opinion, the inbox should have less then 20 emails. The rest is sorted into folders.

I might be old and dull in the sense that I often prefer email communication. I do have my own blog, and I even use IRC from time to time. Yes, IRC, you know the old chat protocol one could use, which didn’t involve in sending all your personal information to third party advertisers.

Note, I do use social sites when I’m off work. Mostly, to keep up with companies I like. For example, I follow Tim Wendelboe (coffee roaster), and lots of artists, so I get the news on what’s up. By the way, Guy Kawasaki has written a book (excerpt in link) for reaching those hip-young-curling-generation, and not to seem clueless on social sites.

Visionary leading

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So, you have some sort of responsibility. It may be work related, voluntary or maybe you plan on taking more responsibility in your own life.

How do you make sure that you have momentum, and a direction according to where you want to go?

Lets consider this: You lead a team of motivated people. You want to make sure the team is getting somewhere.

Get a vision
So what do you do? You need a vision, a higher goal. Point of having a vision, is to say “this is the direction we are heading».

Examples of vision for a team might be: «We are going to be the leading sales team for this company in this specific area». For a personal vision «I am going to become a distinguished doctor».

There is a whole lot to say about this point alone, and theres a lot of articles on the web about how to form a vision, my advise is thus, to start with a dream and build a vision.

Since a higher goal often is quite abstract, you want to break your vision into parts. I call them targets.

Set measurable targets
So, break your vision into measurable targets. You want to measure the momentum and direction of your team. Are we delivering accordingly to our vision?

If you would like to use a business term, it will be similar to a «Key Performance Indicator».

Some measurable targets for your sales team may be «the amount of sales this period versus last period» and «the increase in sales relative to the other top performing sales teams»

Set actions
Actions are where we lose the abstract ideas and get concrete. Specify what you need to do to be able to get to those targets. This is where you brainstorm and get input from other sources. Make sure to get input from people who have come further than you.

My point for today
If you fail at setting a vision or a course, you are probably heading for a mediocre result. It will be harder to know how to measure success. In my opinion this applies especially when you are leading a team, a department, or the likes, but these things are also of worth in what you want to achieve in your personal life.

Predictive Business Intelligence

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Lately, I have spent some time on the future of BI. We know we need reporting, and data warehouses. What about going beyond data warehousing and business reporting?

Instead of asking the question:
How many leads did our last campaign result in?

We turn the question around to:
Which campaign should we run? This question is based on common sense and insight in customers.

Eventually we will ask:
How many leads will our next campaign return? Now, our answer will rely on statistical data.

Hindsight vs Prediction:
“[…]you still need business intelligence to know what really happened in the past, but you also need predictive analytics to optimize your resources as you look to make decisions and take actions for the future[…]”

For more information regarding this topic:
I have found that the blogs at EMC.com provide thoughts and concepts from one of the bigger players in the market. Look up the articles of Bill Schmartzo for more thoughts around this topic.

Source: EMC.com
BI Analyst vs Data Scientist, what is the difference? 

Begin to set focus on predictive analysis. Discover who is the most valuable customers.

Statistical abilities of the Data Scientist.

IT Transformation storymap (in pdf). IT and related processes are always changing. This illustration and its linked articles brings up this topic.