Aiming to provoke thought, provide guidance on your software or analytics journey, highlight business technology advances, and sharing some tips and quick wins too.

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Here are the FAQs

What is the minimum project size that you will accept?

Our project portfolio covers a wide range of clients ‐ from large, global corporate organisations to small, owner managed businesses. To us, a client’s vision and project objective is what matters most, plus we love a challenge. Realistically a reasonable budget investment is needed for a brand-new bespoke system, so if we had to name a

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What does a typical data analytics project look like?

Broadly speaking we follow 6 steps; of course, these may vary depending on the business questions being asked and the data available. Typically, the steps are: Problem Definition Data Exploration Data Preparation Modelling Validation Implementation and Tracking More detailed information is explained in our blog

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What are the main steps in a bespoke software project?

Preparation and Briefing – getting to know each other, your business, and your requirements. Concept and Technical Design – as well as a design specification, we build a clickable framework so you can test and feedback before development begins. Development – building the software in line with customer‐approved milestones. Quality Assurance – testing the beta

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Is Visualisations and Dashboards the best introduction to analytics?

Yes, in most cases. The majority of companies we work with have started their analytics journey with the creation of a dashboard, for example Microsoft Power BI along with some visualisations and correlation plots. This way stakeholders can properly understand the data captured and any gaps that need to be addressed can be easily identified.

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How much time does it take to create a Power BI dashboard?

The costs are very much associated with what you want to achieve and therefore how much time is invested. For example, a simple dashboard, where all data sources are up to date and easily accessible can take will take between 3 – 5 to create and style. More complex dashboards pulling information from a variety

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How long does an average project take?

Typically, an average project will take in the region of three – four months. Some of our projects are small, fully specified and are completed in four – six weeks. Others can take six months or much longer ‐ it all depends on the complexity and scope of the project, and whether revisions, including additional

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How can I get started with data analytics?

Contact us! Objective has a team of data scientists who work on outsourced analytics projects, including proof of concepts and developing visualisations and Power BI Dashboards. Alternatively, we can add skill sets to your in-house technical team. As a starting point what we find works well is a data discovery workshop to understand the quantity

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What are the phases of analytics?

Depending on the stage of the workflow and the requirement of data analysis, there are four main phases of analytics: descriptive, diagnostic, predictive and prescriptive.

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What attributes are needed for a good analytics project?

A data-driven culture, data, time to test and learn and a good idea of what you want to achieve. Data analytics requires a much more in-depth approach to recording, analysing and dissecting data, and presenting the findings in an easy-to-understand visual format.

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How much data is needed for analytics?

Unfortunately, there is not a simple answer to this question. Data is the most important resource for any analytics project. Therefore, organisations need to capture as much business, transactional and customer data in a structured manner. What we find works well is a data discovery workshop to understand the quantity and quality of the data

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How much does data analytics cost?

Data analytics is driven by having a data culture and is typically a long-term strategic decision. The investment is up to you. Many clients initially start with a proof of concept, which can take between 2 – 3 weeks. Then when the results wow them, they are keen to progress to a full-scale data analytics

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