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Email Migration to Office 365 Using a Hybrid Exchange Server Configuration

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This is the first post of a two-part series about best practices and “gotchas” for migrating emails to Office 365/Exchange Online. Usually the two options that come to mind for email migration are:

  1. Cutover Migration
    • In this approach, every mailbox and user is moved to Office 365 at once
    • The challenge here is that there is downtime for emails, and in today’s connected age, it’s just not practical to take this approach
  2. Hybrid Migration
    • This approach is the most widely-used approach
    • A Hybrid Migration makes sure there is minimal to no downtime for emails
    • This approach also allows migration of specific users or sets to Office 365

We’re going to focus on the more widely-used approach of a Hybrid Migration.

O365 migrate

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The Cobra Effect in BI: Part 3

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In my previous two posts I have tabled the concept of the Cobra Effect in BI and taken a closer look at Excel spread marts—the Cobras of BI, and the incentive EDW, aka the single version of the truth.

This week, let’s walk through the journey of creating and rolling out this single version of the truth. Will the EDW incentive prevail over Cobras of BI?

King Cobra Snake, credit: Flickr user Michael Allen Smith

King Cobra Snake, credit: Flickr user Michael Allen Smith

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The Cobra Effect of BI: Part 2

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Last week we started to look at the concept of the cobra effect in BI. This week I want to dive in further and explore exactly what the cobras are in the case of business intelligence.

cobra2

The Cobras of BI or the Excel spread mart: Within each organization, groups of analysts spend endless hours of manual labor producing reports in Excel. A large part of this manual effort is expended in gathering, massaging, standardizing, grouping, segmenting and loading data from a myriad of systems into Excel. Let’s call this first part data consolidation. The remaining effort is spent in creating calculations (several layers at times), Pivot tables, charts and graphs to present and make this data consumable by end users. In this process of producing reports, analysts also conduct analysis, albeit limited but crucial to producing insights for decision making. Let’s call this second part freedom of analysis and insights.  Read more…

 
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The Cobra Effect in BI

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The cobra effect occurs when an attempted solution to a problem actually makes the problem worse. I came across this term in a Freakanomics podcast by Stephen J. Dubner and Steven D. Levitt. The term is used to illustrate the causes of incorrect stimulation in economy and politics. There is also a 2001 book with the same title by Horst Siebert, a German economist and professor.

By the way, I am an avid listener and follower of Freaknomics. I am amazed at their ability to combine research, insights and the fine art of storytelling. It’s an invaluable resource for BI & analytics professionals as we help organizations build data-driven cultures.

The term cobra effect began at the time of British rule of colonial India. The British government was concerned about the number of venomous cobra snakes in Delhi. They offered a reward for every dead cobra that was brought to the government leaders. Initially this was successful as a large number of snakes were killed for the reward. Eventually, however, enterprising locals began to breed cobras for the income. When the government became aware of this, the reward program was scrapped, and the cobra breeders set all their cobras free. As a result, the wild cobra population only grew. The apparent solution for the problem made the situation worse.

Indiancobra

The same problem has happened with rats in Hanoi, Vietnam and feral pigs in Fort Benning, Georgia. In each case, incentive seekers came up with creative ways to maximize their results – and pest populations grew. Incentives don’t always work out the way we expect them to.

So how does this relate to BI? Are there Cobras of BI? Read more…

 
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Self-Service BI is Not DIY

Increasing numbers of companies are pursuing self-service BI to enable their business users to personalize solutions and make data-driven decisions without having to rely on IT. Yet, the industry success rate in this arena is low. Why is this? Choosing the right tool is partly the issue, but the biggest differentiators between companies that fail and those that succeed with self-service BI is knowing where and how to effectively deploy it as a business solution.

DIY

Just say no to DIY

 

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