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Data learning

What is data learning?

 

Data learning takes incredibly huge amounts of data and drives meaningful information from it, such as end-of-year reports, marketing insights, or demand for a new product. It can be performed at the most basic level or involve complex programming and IT solutions. If your business is growing or already serves a large sector of the market, you likely need advanced data learning solutions.

 

Varieties of data learning solutions

 

Depending on your organizational needs, certain data solution might be more appropriate than others. Our options for data learning include:

  • Numerical data

    • Divided into continuous and discrete sectors, these data sets obviously involve numerical figures. Discrete data are represented as whole numbers, while continuous data varies along a scale.

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  • Categorical data

    • Uses certain characteristics to describe classifications and categorize information

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  • Time series data

    • Collected over regular intervals with a temporal value. This data is especially useful when analysing trends.

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Contact us today for your data learning needs in the UK.

Analysing the Numbers

Discover the Secrets of Big Data Architecture

When taking on the construction of a new building, it requires an architect to draw a blueprint. Without this initial step, there's no comprehensive guide to follow during the build. Big Data is no different. Our experience with Big Data architecture can provide the roadmap to aggregate massive stores of information for appropriate, time-saving analytics.

 

Who needs Big Data architecture?

Not every job requires you to work with Big Data. You'll need these services if:

  • you're trying to extract information from large web databases

  • you need to process datasets over 100GB large

  • your company stores a ton of unstructured data that you need to transform for analytics

  • your business or organization wants to utilize big data analytics to make business decisions

 

Steps in Big Data architecture

  1. Big data sources - the environment(s) from which all of your information is derived.

  2. Data massaging and storage - involves collecting and converting any unstructured data in to appropriate formats

  3. Analysis - specific data analytics tools pull out the requested information from the Big Data

  4. Consumption - this is when humans, applications, or others actually look at the data to make sense of it.

To discover the magic of how Big Data architecture can work for you, contact us at Silicon Syrup Ltd. to get started.

Big Data

Although it seems self-explanatory, the concept of big data can be nebulous. It’s daunting to think of all of the information being collected day-in and day-out. How can anyone aggregate and make sense of all of that data, when every single interaction is being recorded?

 

Actually, we have Big Data to thank for many innovative advancements in business. All of this information is invaluable to discern your company’s productivity, the desires of the market, shifts in trends, and so much more. However, in order to make any sort of sense of Big Data, you need the appropriate software.

 

Our artificial intelligence and software strategies can store, translate, analyze, and output that information for use. No matter the volume, uncertainty, variety, or speed at which data comes in - we have a third-party solution for you. Contact us today to learn how mining Big Data can revolutionize your business.

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