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FAQs

How can Snap’s data analytics’ services benefit my company?

Snap helps companies organise their data to ensure that it is in one place so that they can track and measure it and make informed decisions. In large corporations , we have found different teams storing their data in different ways, making it difficult to get important insights when they are needed. Consolidating your data in one place and having a dataset, report or dashboard to reflect your key metrics gives your business the pace it needs, saving vast amounts of time, effort and resources.

How do Snap charge for their services?

Working with data from global corporations we have found that each company has specific needs. In most cases their data starting point is unique, as each situation is different and requires a bespoke solution. Snap excel at unpicking reach company’s challenges through our initial consultation, tailoring a solution and building a team to support its execution. We will talk you through any quotation to answer any questions, agreeing timescales and payment structure ahead of time.

Which geographical areas do Snap cover?

Snap Analytics delivers cloud solutions to many companies around the globe. While we do have our own HQ in Bristol UK, we have remote working as an option. We service a lot of clients in the UK but are always open to increase our reach and influence in Europe, USA and the Middle East. Our partners in the USA and India provide reach across multiple time zones  to work together and give you the team, tools and solutions  you need around the clock.

Which technologies do the Snap team use?

Our staff have the necessary certifications for Matillion and Snowflake, and as a partner of both of these organisations we are always kept abreast of the latest technological advancements and trained accordingly to ensure that our engineers are maximising each technology’s full potential.  We also work across all of the major cloud platforms including AWS, GCP and Azure.  Our analytics capabilities span Power BI, QlikSense, ThoughtSpot, Tableau and Pyramid Analytics and more.

How quickly can you get started?

Our team has grown over the years, enabling our co-founders to focus on consultation, making the most of their insights and experience of using Snowflake and Matillion. In most cases new companies will be dealing with one of our leadership team when looking to start unpicking complex data scenarios and finding the solution best suited to you. After your initial consultation and quotes are signed off our team will start working to the agreed schedule.  Depending on resource availability we typically need around 2 to 4 weeks notice to ensure you have the best team to support your needs.

What is the difference between cloud platform and traditional database?

Like databases, cloud platforms store and process data; the difference between cloud data platforms and traditional databases is that instead of transactional processing, the end-goal with cloud data platforms is end-to-end processing of all types of data including structure and semi-structured data. Cloud data-platforms consolidate data from multiple sources making it useful for data scientists, business analysts and dashboard and report consumers.

What is data transformation?

Data transformation is the process of changing the format, structure, or values of data; taking raw data and making it useful. It can increase the efficiency of analytics and business processes and enable better data-driven decision-making.

What is Snowflake?

Snowflake is a cloud platform that enables you to integrate, analyse, and securely share your data. It’s a fully managed service that’s simple to use but can power a near-unlimited number of concurrent workloads. It’s a solution for data warehousing, data lakes, data engineering, data science, data application development, and securely sharing and consuming shared data

What is the difference between structured and unstructured data?

Structured data, or quantitative data, is highly organised and easily decipherable by machine learning algorithms. Think dates, names, addresses, credit card numbers, etc. Unstructured data on the other hand is qualitative data, which cannot be processed and analysed via conventional data tools and methods. Think text, mobile activity, social media posts, Internet of Things (IoT) sensor data, etc.

What is behavioural data?

Behavioural data captures how people – typically your customers and prospects – interact with your products and services in granular detail. Web and mobile are typical behavioural data sources, but there are many other examples such as email, support desks, chatbots, wearables and SmartTVs.