Having spent the better part of the last decade helping organisations in the U.S. and the U.K. use data to drive profit, efficiency, and performance improvements, I thought it would be helpful to jot down best practices for organizations that are looking to get the most value out of their enterprise-level financial and operational data sets.

Every organisation entering the roaring 20s knows that they must use their data as a strategic differentiator to gain a competitive advantage and…

As a data scientist in an organization you frequently find yourself in a couple of situations:

Many executives struggle to make sense of machine learning (ML) and deep learning (DL). Having a pragmatic relationship with technology, executives need to know on a very fundamental level: "What problems do ML & DL try to solve?" A simple, high-level answer to that question is: "It's all about building systems that do certain things better than humans, with as little intervention by humans as possible." That being said, the simplest way to distinguish between ML and its branch DL…

Business intelligence is important for every business. But, there is a lot of confusion about business intelligence.

This is mainly because BI has been defined in different ways. So, we thought what’s better than talking about business intelligence. We dived into the history pages and compiled a list of definitions and examples that will help you understand this concept better.…

Business analytics is here to stay, and most ventures are wrapping their heads around the idea. Numerous data gets collected from various interactions among clients and potential prospects; Big data is referred to as the complex humongous data. It is not a new fad in the analyst industry. Organization requires making top-notch decisions using big data as an essential component in…

Summary:  Data Scientists from Booking.com share many lessons learned in the process of constantly improving their sophisticated ML models.  Not the least of which is that improving your models doesn’t always lead to improving business outcomes.

The adoption of AI/ML in business is at an inflection point. …

Data is the new fuel- it drives businesses towards exponential growths. It has the power to transform operational and add intelligent insights with its immense potential. The key, however, lies with understanding data and its insights.

Logistics, like other domains, can also leverage from the several advantages of data. It all begins with what to do with the collected data. Data Science will come into the picture with its amalgamation of statistical &…

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…