Most organisations are analysing just 12 per cent of their data and could be missing out on vital insights, according to research by analyst Forrester.
In response, software provider Advanced Business Solutions (Advanced) has published a report offering insight into improving performance through business analytics.
The report offers personal perspectives from Advanced’s business analytics consultants, a team with more than 20 years’ experience of developing big data solutions for organisations in the private, public and not-for-profit (NFP) sectors.
“Advanced has been supporting businesses to implement big data solutions for more than 20 years. Our report provides unique insight based on our extensive experiences and will enable organisations to avoid common pitfalls and reap tangible benefits from their analytics projects.”
Here, Advanced offers the following ten tips for ensuring big data project success:
1. Clean all data first
Avoid the temptation to consolidate data from multiple sources without cleansing it first. Although this may take time it will pay dividends in terms of simplifying report development, reducing project complexities and maximising associated cost savings.
2. Always consider the end goal
Think carefully about any business intelligence goals and the insight which will be of most value to your organisation. Identify priorities such as improving operational performance, understanding customer behaviour or managing risk. Analytics solutions and data models can then be tailored to your exact needs.
3. Ask the right questions
The most valuable insight into business performance is achieved by pre-determining exactly what information is needed and then asking your data specific questions. Many companies implement big data solutions and expect insight without first deciding what they need to know. Vague questions will not receive clear answers.
4. Take a partnering approach
In order to achieve the best results it’s important to work in collaboration with your chosen analytics provider by involving key stakeholders from your own business at the outset. Collaboration will equip you with the knowledge and skills you’ll need to maintain and extend your big data solution in-house in the future.
5. Review before recoding
Work with a specialist and experienced developer to ensure existing reports are formatted in line with those included within a new analytics system. The standardisation of table structures and calculations, for example, will help eliminate inconsistencies which could be costly and time-consuming to resolve in the future.
6. Budget for flexibility, not fixed reports
Many organisations make the mistake of over-estimating the number of reports they need as part of their new analytics solution and this can be expensive in terms of third party development fees. It is far more cost effective to allocate budget to developing a ‘self-service’ solution which enables users to build their own reports as the need arises.
7. Prioritise the executive dashboard
A user friendly interface that provides senior managers with accurate information as easily as possible is key to ensuring the system is used widely. Once you have buy-in from the management team, the rest of the business will follow.
8. Focus on usability to reap greater returns
Ensuring a solution is easy to navigate is essential to producing accurate reports that improve decision-making. If querying a system requires advanced programming skills, it will be side-lined. Work with partners who can demonstrate solutions they have developed which are accessible to non-technical users.
9. Invest in skills, not just solutions
Staff training is fundamental to project success. Teams that are equipped from day one with the skills they need to use a system fluently will ensure a company receives a rapid return on its investment. It can also save large consultancy and development fees for work which can be completed in-house.
10. Never underestimate the impact of an upgrade
Modern back office systems can reduce the time it takes to gather information from different sources and this is key to facilitating business intelligence reporting. Reducing the time it takes to round up information required for reports helps support faster decision-making.
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Duncan, very informative article. When considering a Big Data strategy, companies are faced with data challenges in three different areas. First, you know the type of results you want from your data but it’s computationally difficult to obtain. Second, you know the questions to ask but struggle with the answers and need to do data mining to help find those answers. And third is in the area of data exploration where you need to reveal the unknowns and look through the data for patterns and hidden relationships. The open source HPCC Systems big data processing platform can help companies with these challenges by deriving insights from massive data sets quick and simple. Designed by data scientists, it is a complete integrated solution from data ingestion and data processing to data delivery. Their built-in Machine Learning Library and Matrix processing algorithms can assist with business intelligence and predictive analytics. More at http://hpccsystems.com