Data Solutions


Info Rhino - the data solutions provider

Info Rhino understands how to bring data from different systems into the right place to make it work for you and your business.

Database design for your business

We create data models that works for your specific requirements. We don't always follow the convention because data has evolved. Sometimes traditional database design suits a business, and sometimes it doesn't - we adapt to the requirements.

Building reporting solutions on your organisation's data

Company data can be in many places; websites, accounting systems, Electronic Purchasing Ordering Systems, products databases, and staff systems.

Data audits

We can provide reviews of your existing setup, consider licensing costs and suggest strategies to get the most from information you hold. We advise on; system performance, data quality, and security compliance.

Bringing data to your company

There are millions of potential data sources completely free which you may want to integrate with your own data systems. Simple example - we source all kinds of free data from here - https://data.gov.uk/ .
We can work with you to add data to your company to add extra capabilities to your business.

Streaming solutions

It may be you want a service continually interacting with content. Imagine, you wanted an application to open more gates once more customers arrived, and to reduce the number of gates once those gates subsided. This is what streaming solutions can do.

Your requirements

An idea?

You as a potential customer may have ideas on your requirements, but not have the means to express it. No problem, we can go through a scoping exercise to understand your business, give advice and help you to define a way forwards for your business.
Please drop us an email, we can call or email you back.

A clear vision?

You as a potential customer may have a very strong idea on what you require. New business, new business area, enhance an existing solution?
Great.
Please tell us about it here 

Ideas



 Glossary on common technology in the data solution industry

We wrote this to try and give you a better understanding of how to articulate what you are looking for.

The challenge of industry terminology

As part of rebranding Info Rhino, we looked to other service providers to see what they are saying about their offerings. Even as technology professionals, we found some websites littered with buzzwords and terminology which may alienate most customers. We can think of there being specific terminology or cultural phenomena.

We hope this helps you to find out more about Data solutions.


Business Intelligence

BI brings data from one or more systems which are hard to report from, into a system which makes it easier to report from. Very often, this involves building a data warehouse to house this new data, but it could be a service designed to bring this information together.
Business Intelligence was termed as such, to indicate it gave users the ability to understand "facts" about their operations. Typical facts may be; How many customers this month, how many products sold, how big is the decline in orders for the North East.
Please note, we feel this is the essence of BI.

Data Visualisation

DV is what connects users to the data served by Business Intelligence. It could be a pivot table, a spreadsheet, even a text file. A number of vendors provide dashboards to provide users the ability to navigate different screens and portals to show different elements of their business at different levels. An example could be a screen showing global sales chart, a country sales chart with country selection, a chart showing inflation by product category, and the bottom ten stores sales.

Extract Transform and Load

To be able to develop Business Intelligence solutions, data may need to be processed. The Extract Transform and Load tasks perfectly describes this task. Whilst competent developers can write their own applications to perform ETL, best practice is to use specialised software for this - which Info Rhino are experts in.

Big Data

We don't have too much to say about Big Data. It is just too wide ranging in terms of what it means to different people to comment on.

Machine Learning

Machine Learning is the application of different algorithms to interpret historical data based upon features (inputs) and labels (outputs). ML aims to either; classify, predict or associate relationships between features to predict a label. In a fictional example, we may include features of age and salary to predict the happiness of a person - the label.

Artificial Intelligence

AI is, as it sounds, algorithms that learn from data. A good example is a security camera which has trained itself to recognise people's faces. AI could take a number of songs and then be capable of creating its own songs.

Statistics

A classical field to do which uses mathematics to determine statistical significance versus what can be considered as not exceptional.

Statistics calculator

Geospatial

We always see maps on websites and phones. Geographical points of interest, distances, sizes of areas are to do with geospatial data.

What is a data warehouse?

A data warehouse (DWH) is a specialized store of large sections of a company's data to permit analysis and reporting. We don’t want to go into too much about what a DWH is, but more on why they are useful and why you should use Info Rhino to build your data warehouses.

Main elements of a data warehouse

Data

DWHs contain data, and lots of it.

Dimensions

Think of this as categories of information. A person is a dimension, and they may have a gender, an age, or a credit rating.

Measures

Data that can be counted, summed, or multiplied is a measure.

Facts

This is where measures and dimensions come together to provide useful information. For example, a fact may contain quantity purchased, price paid, customer, date purchased, store of purchase, product name.

Why use a data warehouse?

You may have read our section on databases. A data warehouse solves most of the problems report writers encounter when writing reports against operational databases. As the number of reports required increases, it puts the original database at risk of performing badly.

Are Data Warehouses still fashionable?

The biggest challenge with technology is when new approaches surface, claiming to be faster, better, easier than their predecessor. Big Data was seen as the successor to Business Intelligence and so an entire industry jumped onto the Big Data band wagon. Business Intelligence, is what data warehouses serve and so this made data warehouses appear out of fashion. We think that data warehouses are an essential tool to reporting data within organizations, but as with any other paradigm, care and attention to value gained is required.

The Enterprise Data Warehouse (EDW)

If your organization has an EDW or a CDW, please have a big think about your data and reporting strategy? The chances are, it is consuming lots of data and not producing many meaningful reports at all. Too many times, we have seen huge internal battles between teams, where Team A wants to centralise bringing more to the data warehouse, and Team B where decentralising information into data marts is their perspective on adding more value to the business.

Data Architecture, Data Modelling and your reporting strategy

The correct approach to building effective reporting systems is to model data and to ensure the systems are adequate to contain and deliver data to data consumers. Unlike many zealots, we don't believe Agile to be an effective approach to delivering meaningful systems.

 


 Conclusion on data solutions by Info Rhino Limited

Data can exist in hundreds of different formats, languages, structures and systems. Small Enterprises will benefit from creating a data warehouse, but accepting that data can exist in different locations to a data warehouse is a responsible balanced strategy to getting more value.

Info Rhino develops systems that are more efficient, require less maintenance, and just make sense when it comes to data.