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
Tag Archive for: Data Science
Policing in the United States and around the world is rapidly changing. Just as there have been paradigm shifts in law enforcement procedures in the past, we are now on the brink of another transformation of how communities are policed. Current national narratives and recent events are motivating these changes, and like it or not, a new era of law enforcement is upon us. One of the main solutions that helps law enforcement adapt to this change is adopting a sound data driven policing strategy. Read more
Don’t think you have big data? Chances are you do. The fact is if you have a website, you have big data. Web servers capture and store events related to user traffic. The web logs they generate essentially tell the story of what users did when they visited your site. This information can provide your organization with extreme business value.
If you think you have big data to analyze from your website, you may want to look into Apache Spark. It’s easy to get started with and makes short work of analyzing your web logs. It’s actually pretty fun to work with, too. If you enjoyed playing with LEGOs as a kid, you may have a childhood flashback with Spark. Read more
For the second year in a row, Ironside has been named one of IBM’s Beacon Award finalists, this time in the category of Outstanding IBM Analytics Line-of-Business Solution. This recognition comes in honor of the compelling results that our IronShield predictive policing platform has generated.
IronShield provides turnkey predictive hot spots policing and analytics for law enforcement. It enables data-driven, evidence-based policing that stops crime before it happens and is customizable to the environment in which it’s implemented, going beyond its initial hot spots module to target each community’s needs. Our CEO Tim Kreytak recently highlighted the impact IronShield has had in Manchester, NH helping the city’s police department combat the heroin crisis. Read more
Ironside is excited to welcome Matt Barter into our ranks as our Industry Lead for Crime Prediction & Prevention. As a currently active police officer in an urban New England city, Matt is perfectly positioned to understand the unique challenges law enforcement officials at any level face and uncover the solutions that will let them proactively reduce crime in their communities. Read more
When’s the last time you were talking data and analytics and someone stopped the conversation to ask what a term meant? If you’re wracking your brain now, you’re not alone. It’s a rare situation to run into.
Analytics professionals like being on top of things, which means sometimes when we hear something new in a conversation we just nod and make a mental note to look it up later. And then work gets busy and before we know it we’re resolving to just do our best to pick up said buzzword through context clues in other conversations. Read more
On Tuesday, February 16th, Ironside’s CEO Tim Kreytak spoke to a packed house at the IBM PartnerWorld Leadership Conference in Orlando, FL about the work we’ve done with the Manchester, NH Police Department to help combat the growing heroin crisis in their community not with guns, but with predictive analytics. Following an opening statement by IBM CEO Ginni Rometty, Tim wasted no time in driving home the positive impact our IronShield platform has had. Read more
Suppose you’re trying to build a model to predict respondents, and in your data set, about 3% of the population will respond (target = 1). Without applying any specific analysis techniques, your prediction results will likely be that every record is predicted as a non responder (predicted target = 0), making the prediction result insufficiently informative. This is due to the nature of this kind of information, which we call highly imbalanced data. Read more
Even though we’re already blazing full speed ahead into 2016, it’s always important to take a minute to look back at the past year and recognize the high points that made it special. In addition to being named a Boston Business Journal Pacesetter for the second time, making the Inc. 5000 list of fastest-growing companies for the third time, and receiving IBM’s 2015 Business Intelligence Partner of the Year award, we’ve produced several valuable and popular pieces of thought leadership to enrich the analytics community. Here are the top 5 articles 2015 saw us release. We hope you find them useful as you start your journey into the new year. Read more
Do you ever wonder how Netflix makes recommendations for you? Or how the drug store decides which coupons to offer you when you make a purchase? Behind the scenes they have a data scientist conducting what is called market basket analysis, which searches through vast amounts of purchase history information to find patterns in people’s purchases, web searches, or Netflix viewing preferences. The data mining technique used for market basket analysis is called Association Rules (AR). This is the actual algorithm designed to detect probabilistic if- then statements, such as “If you watched Breaking Bad and House of Cards, then you are also likely to enjoy Mad Men.” Read more