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Empowering our Customers through Data Science

What is Data Science?

Data Science is a discipline that uses scientific methodologies, workflows, models, algorithms and systems to extract

knowledge and insights from data.The Data Science definition can be referenced

back to this paper.

In summary, Data Science is the art of extracting andapplying actionable insights from your data.

“Feature engineering is the process of transforming raw data into features that betterrepresent the underlying problem to the predictive models, resulting in improved

model accuracy on unseen data.”

Dr. Jason Brownlee

THE HUMAN INSIGHTS MISSING FROM BIG DATA

Watch the video

Here are some insightful resources on

Data Science and AI / Machine Learning:

THE BEAUTY AND POWER OF ALGORITHMS

Watch the video

THE BASICS OF AI FOR BUSINESS

Watch the video

Big Data

The term Big Data refers to a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques. In most enterprise scenarios the volume of data is too big or it moves too fast or it exceeds current processing capacity.

Smart Data and Actionable Insights

Big Data has the potential to help companies improve commercial performance and make faster, more insightful decisions. Data can be collected from a vast number of different sources. This data when captured, formatted, manipulated, stored and then analyzed, can provide actionable insights that improve commercial performance,

enhance customer experience, improve operational efficiency and provide infrastructure gains.

The Data Iceberg

“At Attraqt we recognise that there is a data iceberg. We use this term to describe that there is a lot of data that is either available or can

be captured, but what is important is understanding what data is worth transforming, curating and applying in a

systematic way in order to deliver more valuable outcomes. This requires technology to be combined with human ingenuity in a

way that focuses attention on the areas that really matter and can make a significant difference. This sits at the centre of

the Attraqt Advantage.”

Peter Thomas, Chief Technology Officer, Attraqt

Data Science at Attraqt

Our approach to Data Science is to act as the guide and facilitator to our customers; we use our knowledge and architecture to break downthe barriers between business functions and to enable your IT, data science and business users to extract incremental and very tangible

business value from your data.

Data Science Benefits

It is the combination of platform and tools + people and expertise that creates the best outcome. By working with Attraqt, your Data Science initiatives will deliver the following:

Empowering management to make more informed and more

valuable decisions

Better understanding and predicting future trends

Enabling the organisation to better focus on the areas that will

help achieve its goals

Identifying new opportunities to enhance commercial performance

Improving decision making at all levels of the organisation through quantitative data-driven evidence

Testing and validating these decisions to support continuous

improvement

Enabling the organisation to engage with its customers in the

most compelling and relevant way

Assisting the organisation to attract and recruit the right talent

In addition to providing our own ongoing innovative capabilities, we also build strategic relationships with key pioneering vendors. These relationships provide us with innovative technologies that together enable us to create new leading-edge product features and capabilities that provide our customers with a distinct competitive

advantage in the marketplace.

The Fredhopper Discovery Platform has been established with an open architecture and an extensible framework. A key component of the platform is our Smart Data Engine and this enables us to place Data Science at the centre of our value proposition. The Smart Data Engine enables our customers to:

DISCOVERY PLATFORM

COLLATE & CAPTURE RELEVANT DATA

TRANSFORMTHE DATA

VALIDATETHE DATA

MAKE THE DATA AVAILABLE

In addition, our customers are able to engage with our Experience Optimisation team to help identify what data to capture and how to transform and apply this data into actionable insights.

Key components of the Fredhopper Discovery Platform

SMART DATA ENGINE RELEVANCE ENGINE MERCHANDISING STUDIO

Unified smart data integration, transformation and application to unlock real-time shopper

intent and interests.

Discover Actionable Insights through application of machine learning algorithms

and smart data.

Enables merchandisers to seamlessly collaborate through a best-in-class UI to

deliver strategies, creativity and inspiration.

CREATE NEWDATA POINTS

Empowering your approach to Data Science

Our customers benefit from a Platform that is designed for maximising the value that can be delivered through Data Science initiatives

Open architectureOur architecture is highly configurable so you can inject data from multiple sources with limited resources and within a tight timeframe.

Rapid innovationOur extensible architecture enables customers to experiment using agile methodology in order to try things out, deploy rapidly, learn fast and

enable a culture of continuous improvement.

Client customisationOur platform approach to APIs also means that customers can inject and use their own algorithms to further optimise the smart data to deliver even

more outstanding outcomes for the shoppers, whilst improving commercial performance.

Data Science Examples

The Smart Data Engine is where we deal with various methodologies to extract meaningful attributes or features from the raw data after it has gone through necessary wrangling and pre-processing. This delivers Feature Engineering that is core to building any intelligent system.

“Coming up with features is difficult, time-consuming, requires expert knowledge. ‘Applied machine learning’ is basically feature engineering.”

Prof. Andrew Ng.

COLLATING &

TRANSFORMING DATA

Providing our customers with the Smart Data Engine to combine, centralise and enrich multiple

separate streams of rawdata input.

Fashion

INCORPORATING CLIENT

ALGORITHMS

Consuming data that has already been collected, transformed

and applied as insights to give customer’s business teams the

ability to curate the way in which this data is applied.

Pure Play Fashion

INCORPORATING CLIENT’S

SMART DATA

Consuming customers’ own smart data and providing customers’ business teams the ability to

blend this data to inform their strategies via the Merchandising

Studio.

Premium Fashion

Here are some key examples of how our Smart Data Engine and Machine Learning algorithms areassisting our customers to become leaders in Data Science application.

Our Smart Data Engine can handle handle all and every form of data to deliver best-in-class Feature Engineering, including:

Ability to use customer data to create new data points for analysis

Obtain data from third parties and tying that precisely with product data to ensure analysis is correlated correctly

Merging search data with product catalogue or content data to suggest relevant data for additional analysis

The amazing thing is we can deliver all of the above all at the same time.

Contact usTelephone: Email: Website:

+44 20 3675 7800 sayhello@attraqt.com www.attraqt.com

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