Business Intelligence Blog from arcplan
14Nov/140

Top BI Trends Moving into 2015

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With 2014 coming to an end faster than anyone could ever imagine, the time to start thinking and planning for 2015 has fast approached us. With the start of a new year comes a number of technology changes to consider. With the following new BI Trends, Business Intelligence (BI) should not be on the long list of things for any organization. While some of these trends are already being implemented, with the potential to expand over the next year, there are a number of proposed changes that could fundamentally shift business processes. Below we will uncover what to expect when looking into BI trends for the year of 2015. Continue reading this post>>

6Mar/140

Examples of Business Intelligence Use Cases

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business intelligence While it might seem like every company on earth is using business intelligence tools to glean insight from their corporate data, surveys say that nearly 10% of companies do not yet have BI in place. Even though 91% of companies may have it deployed somewhere in their organization, anecdotally BI vendors like to trot out the statistic that only 20% of potential users have access to business intelligence. The more companies we talk to, the more this seems true.

If you run a company or a department that doesn’t have access to BI tools, you might wonder how you can use them. Boris Evelson from Forrester Research compiled a list of analysis types that may apply to your situation:

Analysis Types

  • Historical (what happened)
  • Operational (what is happening now)
  • Analytical (why did it happen)
  • Predictive (what might happen)
  • Prescriptive (what should I do about it)
  • Exploratory (what’s out there that I don’t know about)

When you’re first starting out with BI, you’ll likely be most interested in historical and operational analytics, though we often work with finance teams who want to dive right into predictive analytics. Let’s look at a few practical BI use cases in various departments of an organization.

Finance Department: Historical, Operational, Analytical, and Predictive Analysis

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22Nov/130

3 Big Data Considerations for Newbies

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big-data-newbiesSixty-four percent of organizations are already investing in or plan to invest in big data soon according to a recent Gartner report.* That equates to a huge number of individuals who now have to research how to embark on a big data deployment. The prevalence and benefits of big data analytics are undeniable, but there are some considerations to keep in mind before jumping in:

1) Identify a specific business need

Big data projects reap the most benefits when they address specific business needs. Having a use case in mind will help determine what data you need to analyze – social, machine or transactional data. Gartner recommends researching use cases and success stories in other industries; why not get inspired by what’s worked for others? Gartner analyst Doug Laney recently shared examples of big data at work in various industries: using big data analytics, the department store Macy’s was able to adjust prices in near real time for 73 million items based on demand and inventory; Wal-Mart was able to optimize search results and increase web checkouts by 10 – 15%; and American Express used sophisticated predictive models to analyze historical transactions and forecast potential churn. Once you’ve identified the analytic need not met by “small” data analysis, you have the first green light for considering big data technology.

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