You arrive in a foreign city for a couple of days and you need to get some stuff done and attend some meetings. You have no idea how to move around and you don’t speak the language, nor you are able to drive. Yet, people approach you to sell you a car, competing on the features and capacity of their offering, then also giving you the opportunity to take some lessons so as to be able to take ‘full advantage’ of it. You end up paying a lot of money for the high-end car and wasting your stay in attending driving seminars; yet you still are not able to navigate around and you missed those meetings, you are finally told that the city is to blame.

compass - a photo by flickr and user maldita la hora

The above story probably sounds peculiar and the approach taken is awkwardly wrong; after all it doesn’t take that much of intelligence to simply get a taxi or hire a driver for those two days. Still and to our surprise, this is how the enterprise world works when it comes to selecting a data mining solution or tackling a data intensive problem, and we’d like to serve our fair share to try and shed some light, given our very limited experience thus far. Here’s the original version of the story:

A big enterprise wants to leverage the big amount of data it collects so as to get actionable recommendations with regards to some pressing topics of its operations. The company does not have the talent, nor the experience and expertise to handle that, so it starts looking for external partners. Typically, these end up to be big software vendors and their certified partners, providing ‘holistic’ and ‘customizable’ solutions to every specific problem on earth. The managers get excited; these solutions seem to provide everything they need to feel comfortable about, including a complete stack of algorithms, full integration with their CRM and existing intra-enterprise infrastructure, also a well-known brand and tons of phone support staff. So, they proceed to sign the really fat check and assign the rest to their colleagues.

It takes a few weeks for the vendor to set everything up, then the various modules turn out to be quite complicated and the manuals non-readable at all, so the company proceeds to also pay the extra specialized training partners to educate some selected people of its personnel on how to import data and what to click for an algorithm to operate. Now that they know how to put the tools into action, the company is finally able to get back to the original problem and try to come up with a working solution. But, guess what, they own the Ferrari, they know how to drive it, but they have absolutely no clue on how to navigate across the chaotic city, or interpret the various signals to get the job done!

Data mining software is not the equivalent to, say, Microsoft Office. If you have some basic Word skills, you’re probably able to write and edit a text document; however, if you know where to find the Support Vector Machines button in a data mining suite, you’re still far away from coming up with any working solution to your problem. Trial and error, standing at the core of anything related to data mining, requires a deep understanding of the underlying processes behind each one of the numerous algorithms, enabling you to follow best practices on every step, pick the right instruments and be able to interpret the results so as to proceed to the right direction and improve, from naive results to really insightful ones. After all, in experimental problems, the tools are not the ones which matter the most; actually they do not matter at all if there are no experts to put them in good use.

At the end of the day, experts are needed to tackle such sophisticated problems, and our humble recommendation is to start with them, and then decide on which tools you need to acquire, if any at all. You may also consider that, in most cases, data mining is not a task that you need to pursue on a daily basis; capable resources are required into solving a problem once, then you just replicate its solutions across time. Moreover, since you have acquired good results, there’s typically no need for an expert to replicate these into new data sets; you may just run an already available black box of code, or implement some fully transparent recommendations using naive tools, like advanced filtering. After all, it typically makes much more sense to get a taxi to move you around than hire a full-time driver and have him waiting till the next time you happen to be in town.

We do believe that the above may help you to get a better understanding of how things work, or actually should work, in the industry and what dead end solutions you need to avoid. In any case, we’d happy to show you around and help you find your way next time you’ll get lost with data or you happen to land in the far-off area of data mining, rest assured that there lies really great value waiting to be discovered!

Inventory management is your daily business. Optimized usage of your limited resources is your holy grail. At the same time, you are drowning in data, still thirsting for the actionable knowledge you can extract and directly utilize out of it. And that’s just what Mineknowledge is about to offer.

photo by flickr & user nutmeg

Supply chain management is tough. Products come and go, inventory grows and shrinks, but you have yet to take action on the patterns (that you observe) taking shape over time. Simultaneously, both inventory and opportunity costs increase, while monitoring data get accumulated along with wasted opportunities for performance improvements.

We can help you turn such data into actionable insights and tap on the knowledge lying beyond. Logs of inventory input and output, data per product, retailer, area or time period, in short any dataset ranging from a simple excel file to a huge database can help us to deliver tangible recommendations and you to improve the efficiency of your daily business. Examples of outcomes may include:

- Improved estimates of demand per unit of interest (quantity, price, date etc)
- Pattern extraction of what triggers desirable results, or not
- Key performance indicators structuring and correlation to measurements of interest
- Specific advice and recommendations on improving performance across the supply chain

If you want to bring the level of your business intelligence from monitoring to action, Mineknowledge helps you deliver; contact us for more at goATmineknowledge.com

You are using the latest instruments and techniques to ensure best quality results for your patients. Yet, you almost feel overwhelmed by the ever growing list of indicators that you need to monitor, before you are able to confirm any of your judgments. At the same time, you keep trying to give shape to a number of your insights and hypotheses, which yet you are not able to somehow verify. We can help you address all of the above, plus more.

photo by flickr & user gonzales2010

Deciding on medical treatment has matured to be -on top of everything else it used to- a data intensive task. Patients nowadays come together with a really big volume of data; among others, their general characteristics, treatment records and various status monitoring indices, all of which need to be considered in parallel with the track record of all treatment alternatives. In short, on top of their challenging job, health professionals are now required to excel in statistics, too. We can be of help.

Mineknowledge provides you with a set of medical services, including:

- Healthcare management: decision support on high risk patients identification, also reduction of hospital admissions and claims
- Diagnosis of best practices: study of historical data suggesting efficient versus incompetent treatments, supported by quantitative results; also pattern detection and confirmation or discovery of medical hypotheses
- Ease of information overload: formation of aggregated indices, enabling quick supervision of medical status, while securing improved levels of accuracy
- Research: support on data intensive tasks, spanning from genomics to clinical research to public health

The above stand as a small subset of Mineknowledge services for healthcare; contact us to shape a custom solution for your very own needs.

Marketing matters to you. Targeted and efficient marketing fuels your business, bringing in the clients looking for you, while expanding the essence of your brand. Still, you lack the tools and processes enabling you to exploit the customer data you accumulate over time, leaving you no option but mass and costly campaigns. We help you do quite the opposite, and consistently deliver.

shopping cart, by flickr & big gray mare

Sales and customer data collection has been a requirement for your daily processes, yet one can safely bet on such data being underutilized, if at all. The fact is that there lies a tremendous wealth of information, capable to help you in both your strategic and day to day decision making with regards to marketing and sales. Mineknowledge experience and expertise serves you to exploit this untapped potential.

Here are some parts of the solution we bring on the table for you:

- Market Basket Analysis: Discover how your products are related to one another, which purchase leads to the next one plus more.
- Behavior Analysis: Explore the hidden patterns behind your customer’s purchasing habits, also how you can trigger such behaviors.
- Customer Clustering: Find out groups of customers with similar characteristics, enabling fully targeted marketing activities.
- Risk Profiles: Study the risk profiles of customers and products, to get sound quantitative estimations on what to expect and how to plan accordingly.

Intrigued or still in doubt, you may just contact us at goATmineknowledge.com to get more info and discuss over your specific details.

You have a considerably large list of customers which you want to exploit as much as possible in terms of introducing new services, turn pay as you go customers to contract etc. Or you are pursuing mobile marketing, and you need to optimize the vast amount of sms you send. Which customers are likely to respond better to different type of products and offers? Answers lie in data.

mobile phone, by flickr & roozbeh rokni

Mineknowledge can provide detailed analysis of your database and help you design effectively your marketing campaigns and products in terms of targeted sales. In more detail, we can help on a number of issues like the following ones:

• Segmentation of customers depending on their behavior and characteristics
• Improve response rates of customer contacts
• Improve customer loyalty
• Reduce churn rate and increase revenues per customer

Having served a number of high end international companies in this space, Mineknowledge has built experience on top of its expertise on this vertical, and we’d be happy to discuss more and shape a highly customized solution for your company’s needs upon request.

Every day you are dealing with crucial decisions like providing credit cards and loans or not, how much should the credit or insurance limit be and so forth, each time depending on your data and relationship with the customer. We can help you be more efficient and comfortable with your frequent decisions.

credit card, by flickr and user barsen

Mineknowledge has the tools, experience and expertise to securely study the data you have accumulated over time, extract hidden patterns of client behavior and come back to you with actionable insights and recommendations for each one of your existing or aspiring clients. Here are some more details of our banking & insurance services:

• Customer segmentation: Identify customers with predefined characteristics. The aim is to find the most profitable and least profitable segments in order to create products and services, which can be specifically marketed and sold to those segments.
• Credit risk: Reduce risk in portfolio, develop scoring models that reduce loses by predicting bad loans, understand the profile of “good” customers in order to maximize profits, also reduce risk which comes from misbehavior (like fraud cases)
• Targeted sales: Understand each customer’s business opportunities and risks as a base for more efficient and profitable personalized interactions.
• Marketing and sales actions support: Extract data from the company’s data warehouse and highlight customers with specific characteristics in order to exploit it in CRM Campaigns and other marketing channels.

Should you wish more details, please contact us for more information at goATmineknowledge.com.

For those of you with a quantitative background, or in the happily case that you’re not turned off with the technical details, here’s a rough list of the tools and techniques we typically use when putting our hands on customers data.

toolset - by flickr & user flattop341

• data cleaning & transformation
• creation and maintenance of large databases
• definition, design and production of data attributes
• descriptive statistics
• data visualization
• time series analysis
• survival analysis
• multiple regression
• analysis of variance/covariance
• generalized linear models
• correlation analysis
• cluster analysis
• factor analysis
• principal component analysis
• multidimensional scaling
• statistical quality control
• unsupervised and supervised pattern extraction
• classification and clustering techniques
• association rules
• decision trees
• predictive data mining
• neural networks
• support vector machines
• recommender systems
• bayesian analysis

Let us also stress the extensive effort we each time put on interpreting the results of all the above techniques. So, rest assured that the outcomes we deliver are engineered to be easily comprehensive and directly actionable, free of jargon or any other technicality you won’t be perfectly comfortable with.

Should you want to learn more or discuss how these apply in your specific data and tangible problems, shoot us an email at goATmineknowledge.com

You interview lots of people, you conduct focus groups and send more or less structured questionnaires. At the end of the day, you gather lots of data and you are expected to deliver great insights and outstanding results. We help you do better and more.

Surveys, a photo by flickr and hfabulous

Mineknowledge builds upon your data to provide you and essentially your clients with extra layers of analysis, bringing latent conclusions to light and the added value of your services to levels you hadn’t experience before. Putting machine learning and artificial intelligence techniques to your service, we also take care and filter out any extra complexity, providing you with filtered and easily comprehensible results, ready to append for end user consumption.

Some descriptive examples of our analyses include:

• multi-variable pattern extraction and high level interpretation
• segmentation of users, products etc
• predictive rules
• behavior modelling

To get a more clear view, you may just take a closer look at the indicative cases provided here, or you may just email us at goATmineknowledge.com to work together on the details.

Ria, 25, holds a Diploma in Applied Mathematics and Physical Sciences from National Technical University of Athens (NTUA). She focused her Diploma Thesis on Mathematical Modeling for Policy Making, while she continued her studies with an MSc in Applied Statistics, again at NTUA. Her research interests expand into areas such as Corporate Social Responsibility Assessment and Corporate Fraud Detection, while her professional experience includes serving as data analyst for a forex brokerage firm and an international consulting firm.

Ria is a co-founder of MineKnowledge Ltd, and one of the core data engineers of the team.

Athina, 24, holds a Diploma in Applied Mathematics and Physical Sciences fro National Technical University of Athens (NTUA). She continued her with an Msc in Applied Statistics from NTUA and an Msc in Communications Engineering and Signal Processing from Imperial College London. She has conducted three diploma thesis in the areas of WiMAX networks, generalized linear models and routing protocols for ad hoc networks. Her latest interests, apart from data mining, focuses on analyzing large databases with the help of SAS.

Athina is a co-founder of MineKnowledge Ltd, and one of the core data engineers of the team.

Find Athina around the web at:

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