The BI Tool Roundup: Finding What Fits

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The BI software market is continually becoming larger and more complex to navigate.  Any organization looking to implement, update, complement, or replace BI tools has surely been inundated with information from dozens of vendors offering potentially hundreds of business analytics technologies.  How does one begin the process of narrowing the playing field and choosing the right solution?

Ironside is here to help. This article represents our thoughts on what to look for in a BI tool and explores some of the tools we think work well in different business cases: Birst, IBM Cognos Analytics, Microsoft, MicroStrategy, Qlik, and Tableau. Read more

Social Media Analytics: Unlocking Your Audience

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According to Dave Chaffey’s 2016 global social media research summary, over 2.3 billion people actively use websites like Facebook, Snapchat, Twitter, and LinkedIn to view content or engage with other users . This massive audience represents a huge opportunity for organizations to understand what trends they can connect with, who their ideal customers are, and what the sentiment is around their brand in the marketplace. These insights all become possible through social media analytics. Read more

Ironside Presents at Boston Scalable R Analytics Meetup

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Ironside experts Dan Gouveia and Chi Shu recently got the chance to share knowledge with our local analytics community at the Scalable R Analytics Meetup in Cambridge, MA. Presenting to a packed room, Chi and Dan dove into several ways that R’s powerful data science capabilities could be scaled to apply to much larger, enterprise-level data sets. They demonstrated how to achieve this scalability both with dashDB, a cloud data warehouse, and Spark, a big data-oriented parallel processing framework. Read more

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Ironside Webinar Series: Discover a Smart, Simple Way to Aggregate and Visualize P&C Risk

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On June 23rd, Ironside hosted a webinar with Pitney Bowes on how to gain valuable insight when you seamlessly integrate Location Intelligence and business analytics.   Crystal Meyers, BI Engagement Manager with Ironside and Heidi Geronimo, Principal Product Manager for LI with Pitney Bowes presented on how Location Intelligence, regardless of size, is a strategic priority for insurers, especially in the Property & Casualty area.

Insurers need precise efficient ways to aggregate, visualize, and assess P&C risk.  We will review what can be done to diminish these risks and show a live demo of a risk aggregation solution which was designed specifically for P&C Insurers.

Read more

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The Newbie Data Science Guide: Beginning Advanced Analytics

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Many of you have heard buzzwords such as “data science,” “big data,” or the “Internet of Things” before. You’re able to piece together that these fields relate to each other and deal with analyzing data in some way, but maybe you’re not so sure what these terms really mean. That’s what I’m here to help with.  As a newer member of the data science field, I developed this short data science guide based on my experiences and perspectives in an effort to help those who are just starting out. Read more

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Ironside and Domo Partner for Flexible Self-Service Analytics

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Ironside’s partners help us empower our clients and deliver value from data and analytics using the best technology for their particular business needs, which is why we’re excited to announce that we’ve added Domo to that list. Domo’s flexible, collaborative, and intuitive platform represents a strong approach to modern self-service analytics, and being a Domo partner lets us bring our clients actionable insights from diverse data sources even in low-IT environments. Read more

Domo Marketing Analytics: A Case for Rapid Data Discovery

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Domo is a tool that has stood out among the many data discovery-oriented analytics solutions now hitting the market thanks to how quickly it can have a practical impact on specific functional or industry business cases. It represents the realities of modern business:

  • The questions organizations ask to support decision making are constantly evolving.
  • Traditional business intelligence (BI) solutions aren’t flexible enough to cope with the speed of these changes.
  • Business leaders need tools that enable them quickly, not tools they fight to use.

Read more

Ironside Case Study: RSA Builds Sales Rep Trust with SPM

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In the age of cloud-based applications and anytime access across many devices, having digital security in place that’s smart, flexible, and reliable is essential. Every day, RSA sales reps help businesses meet these requirements with industry-leading security solutions, providing them with the peace of mind and confidence needed to be successful. RSA in turn wanted to give reps that same level of certainty about their compensation payouts so that they could move from deal to deal without having to worry about the accuracy of those numbers. Ironside’s Sales Performance Management (SPM) team partnered with RSA to help make this a reality. Read more

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Ironside Tech Tip: Show Cube Sizes in BI Reports

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Cubes (including Cognos PowerCubes and Dynamic Cubes, as well as other file-based cube technologies) are well-known, commonly used, and valuable data sources in reporting.  As specially indexed binary files, report performance with cubes is generally robust, however when cube files grow very large (or there is high simultaneous demand reading from the cube), response time can and will decrease. That’s why it can sometimes be useful to show cube sizes on BI reports to let authors know when a cube’s size could be affecting performance. Read more

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Why to Use Spark for Data Prep and Machine Learning

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The immense amount of data being collected today, in any industry, expands the reality of advanced analytics and data science. In concept, it creates an explosion of opportunities and expands what can be accomplished. In reality, we are often limited in scope by our data processing systems which may not be able to handle the complexity and quantity of data available to us. The introduction of Spark has offered a solution to this issue with a cluster computing platform that outperforms Hadoop. Its Resilient Distributed Dataset (RDD) allows for parallel processing on a distributed collection of objects enhancing the speed of data processing. For this reason, Spark has received a lot of interest and promotion in the world of big data and advanced analytics, and for good reason. Read more