Imagine you’re completing a mission in a computer game. Maybe you’re going through a military depot to find a secret weapon. You get points for the right actions (killing an enemy) and lose them for the wrong ones (falling into a pit or getting hit). If you’re playing on high difficulty, you might not conclude this task in just one attempt. Try after try, you learn which consecutive actions are needed to get out of a location safe, armed, and equipped with bonuses like extra health points or…

Summary:  Whether you’re a data scientist building an implementation case to present to executives or a non-data scientist leader trying to figure this out there’s a need for a much broader framework of strategic thinking around how to capture the value of AI/ML.

There are many articles written from a tools…

BigQuery is Google’s serverless, highly scalable, enterprise data warehouse designed to make all your data analysts productive at an unmatched price-performance. Because there is no infrastructure to manage, you can focus on analyzing data to find meaningful insights using familiar SQL without the need for a database administrator.

Analyze all your data by…

1. Background

New home construction plays a significant role in housing economy, while simultaneously impacting other sectors such as timber, furniture and home appliances. New house sales is also an important indicator of country’s overall economic health and direction. In the last 50 years there has been few significant bumps and turning points in this sector that shaped the trajectory of the overall economy.  Here I review the…

Summary:  Digital Decisioning Platforms is a new segment identified by Forrester that marries Business Process Automation, Business Rules Management, and Advanced Analytics.  For platform developers it’s a new way to slice the market.  For users it eases integration of predictive models into the production environment.

As…

Data has become a cargo cult. Collect more data, calculate more metrics, hire more analysts, let them figure out what this is all for – and you’re considered to be data driven. I've had it up to here while consulting startups over the past three years and helping them to define business…

In a previous blog I wrote about 6 potential applications of time series data. To recap, they are the following:

1. Trend analysis
2. Outlier/anomaly detection
3. Examining shocks/unexpected variation
4. Association analysis
5. Forecasting
6. Predictive analytics

Here I am focusing on outlier…

A time series is a sequence of data points recorded at specific time points - most often in regular time intervals (seconds, hours, days, months etc.). Every organization generates a high volume of data every single day – be it sales figure, revenue, traffic, or operating cost. Time series data mining can generate valuable information for long-term business decisions, yet they are underutilized in most organizations. Below is a list of few possible ways to…

Sometimes when dealing with performance metrics, there are contradictory signals.  For instance, although both are desirable, it is common for efficiency and efficacy to be in opposition.  An agent in a call centre can handle lots of calls while at the same time getting few sales; this is especially true if the agent’s main objective is to do lots of calls.  This is a highly efficient person albeit unsuccessful in terms of expanding the business.  Conversely, another agent by spending a…

The following simulation is based on a presentation that I attended in the 1990s.  I was an investment junkie back then.  I sat down, and I listening to people speak about their ideas on making money - on television and sometimes live.  The presenter in this case was trying to explain that investment success is sometimes a matter of chance.  He had people in the audience stand up.  He asked them to guess heads or tails.  Those that were correct continued to the next round - to guess again -…

Many of “out-of-the-box” analytics solutions come with automatically defined user sessions. It’s good to start with, but as your company grows, you’ll want to have your own session definitions based on your event data. Analyzing user sessions with SQL gives you flexibility and full control over how metrics are defined for your unique business.  

What is a session and why should I care?

The session is usually defined as a group…

The term “technical analysis” usually refers to the study of stock prices.  A technical analyst might use real-time or closing prices of stocks to predict future prices.  This is an interesting concept because of what is normally excluded from the analysis - namely, everything except prices.  Given that the approach doesn’t necessarily consider the health or profitability of the underlying companies, a purely technical approach seems to offer guidance that is disconnected from reality.  Yet…

Quite recently we’ve built event analytics for our team and thought to share this experience with you in this post .

Many of “out-of-the-box” analytics solutions come with automatically defined user sessions. It’s good to start with, but as your company grows, you’ll want to have your own session definitions based on your event data. Analyzing user…

The Statsbot team estimated LTV 592 times for different clients and business models. 

Customer lifetime value, or LTV, is the amount of money that a customer will spend with your business in their “lifetime,” or at least, in the portion of it that they spend in a relationship with you. It’s an important indicator of how much you can spend on acquiring new customers. For example, your customer acquisition cost (CAC) is $150, and LTV is…

I once posted about making use of narrative objects.  In this blog, I will be discussing an algorithm that supports the creation of these objects.  I call it my “Infereferencing Algorithm”: this term is most easily pronounced with a slight pause between “infer” and “referencing.”  I consider this a useful and widely applicable algorithm although I don’t believe it operates well in a relational database environment.  Instead, I use “mass data files”:  these contain unstructured lumps of…

You’ve perfected your CV, got great experience under your belt, maybe a PhD and can wrangle data amongst the finest but just how prepared are you for your next interview?

Just the thought of the face-to-face interview stage is enough to strike fear into the bravest of us.  Here are a few things to keep in mind and stave off the sweaty palm syndrome. (Bonus tip – if you are prone to perspire through the palm, remember to use a…

Many of us trust our gut feeling implicitly.

We have all been there when something didn’t feel right but done it anyway. There was nothing obvious to suggest that it was a bad idea. Yet, when it turns out to be a disaster we wonder why we didn’t listen to that gentle little voice: “don’t do it.”

It seems that our gut feel is some magical force, but actually, it is an accumulation of thousands of tiny past moments, all informing our current situation. You could…

And what we can do about it…

“The problem is that, in many cases, big data is not used well. Companies are better at collecting data – about their customers, about their products, about competitors – than analyzing that data and designing strategy around it.”  –

How can this still be the case? I mean after 5+ years of experience with Big Data, have we not learned a darn thing? We get the following observation from no less than the Harvard Business School:

The new…