analytic community
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CIO’s globally ranked analytics and business intelligence as one of the most critical technologies to achieve the organisation’s business goals, with data and analytics skills topping the list as the most sought-after talent. As we embrace digital transformation, it’s clear that the need to upskill and resource data science teams has become far more pronounced.

Building a successful and lasting data community can often be one of the most significant hurdles to overcome, which takes time and effort. Often establishing and maintaining a thriving collaborative approach to analytics, with the right ecosystem for your community, can be a challenge.

Naturally there’s a growing need to ensure analytic teams have access to the best tools and latest methodologies to perform their analysis and find business wisdom. Alongside identifying the analytics skills already in place, a great place to start is also to identify the best tool for the job.

Nurture and aligning members of the community

Pulling together existing disparate data science resources into a single, connected community of practice, creates a secure foundation to grow analytic talent. Having such a community means the business will have a better understanding of the skill sets that exist within the organisation already, as well as best practice examples for approaching different scenarios and a better awareness of the tools and solutions that can be used.

Defining the right tools for the community

R and Python are still the two most popular and adopted programming languages. Both tools are open source, free to use and cover pretty much everything data science-related.

R was developed specifically for statistical analysis, so naturally is the popular language choice for statisticians. R has a large user community and an actively developed large library of packages which enables effective analytics. However, R can require a steeper learning curve and people who do not have prior programming experience may find it difficult to learn.

Python on the other hand, is considered the easier of the two most popular languages to learn. Its domination in machine learning is well-known. With an increasing community base, Python is commonly taught in Computer Science lessons in Schools and therefore the rated language of choice in academia. However, Python can be considered to have its limitations especially around speed and memory, so best practice use should be applied when considering Python.

It’s not a debate as such on which language to use, but more a conversation around empowering a team to become multilingual and multiskilled, so they can use the best language for the application.

Up-skilling of analytic talent

For an organisations analytics function to thrive, it’s critical to continually attract, develop, and retain key data skills & capabilities. Understanding the mix of skills within a data science team, as well as identifying gaps to unify skills & knowledge, is vital to drive analytic value. Establishing the support of a dedicated Learning and Development partner, who provides live, instructor led, data science training programmes, designed to equip and enthuse a data team with the latest approaches, can help address this challenge & unlock business gold.

Enabling training at all levels of data awareness will be critical, and this should even include training on how to use information, to guide decision-making.

Building a successful community provides a solid basis for working out where the talent pool needs to be extended, unifies talent across the business and enables quick wins towards embedding the right culture and building the required capability.

After 20 years of experience, we are a trusted data science L&D partner to leading brands worldwide. We train thousands of data science and analytical teams every year from a range of industries and backgrounds.

 

Beth Ashlee Senior Data Scientist
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A worthy nomination for Beth Ashlee as we receive news of her nomination for the Data IQ New Talent/ Data Apprentice Award.

As an instrumental member of our Mango’s consulting team, we’re keen to share her journey from Summer Intern to Senior Data Scientist within an impressive 5 year time frame.  We all aware that the field of data is a fast moving, but Beth has achieved a phenomenal amount in her time with us.  With each experience, she has shown a remarkable desire to learn from it, evolve and nurture both her consultancy and technical competency and so we believe this shortlist is worthy of recognition.

Beth’s accomplished engagement style

As a master communicator, Beth excels in her role as a consultant at Mango using her empathetic communication style – enabling her to establish meaningful relationships alongside the ability to easily translate business value across an organisation.

She has demonstrated the ability to easily adapt to an ‘insourced’ team leader role or team lead as part of an ‘outsourced’ project and as a naturally competent people person, she makes everyone around her feel valued and motivated.

Beth is one of Mango’s standout Senior Data Scientists, and after a succession of promotions now leads and mentors the Graduate team in both a technical and personal development capacity. Demonstrating a ‘role model’ leadership style, it’s easy to see why all of our graduate cohorts across the past 2 years have developed into capable and credible data professionals that are proactively supporting the growth of our business today.

Congratulations Beth on your achievements, we certainly look forward to celebrating with you at the Data IQ awards night on 30th September.

virtual training blog
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“Education is the passport to the future, for tomorrow belongs to those who prepare for it today”. Malcom X

As Nelson Mandela acknowledged, education is truly the most powerful weapon which can be used to change the world. This year especially, we’ve all experienced the need to be agile, to adapt to changing circumstances and recognise how upskilling and learning is essential to expanding our capability to meet an ever-adapting environment.

It is upon foundations such as these that Mango has built education solutions on; working with data science teams to build future proofing skills aligned to strategic objectives.

A recent survey by Udemy noted the recent and specific emphasis on upskilling and reskilling as a result of the pandemic, with 62% of organisations aspiring to close their skills gap. A key starting point for business is in assessing the skills needed to meet their strategic aims and business objectives. In addition, they need to consider the diverse capabilities across their teams, to truly embrace the right learning culture. Team building and upskilling is an integral part of embracing change for a data-driven future. According to the report by Udemy – data literacy is the new computer literacy.

Workforces with strong data skills across the organisation, not just limited to the analytics team, can help embrace these positive changes. Quite often, it’s the business stakeholders who own the targets and processes who are most empowered by engaging in the data & analytics conversation.

As educators in data science and advanced analytics, we’d like to share some of the most effective strategies when looking to upskilling teams and business stakeholders appropriately:

  • Ensure a dynamic, facilitated learning environment – This year, like no other before, saw providers going virtual. Whilst nothing replaces face to face contact, any method that brings your teams together virtually into a real classroom setting, is the next best thing. Applying learning to a workflow requires a mentoring-based approach to help build lasting and best in class capability. Self-learning or pre-recorded lectures have their place but lack the interactive ‘in person trainer’ approach, where wider questions can be answered.
  • Apply a unique learning experience so that it is tailored to the market or industry – the ability to adapt to the needs of a diverse group is a core skill as a trainer. Practice exercises tailored to help beyond the classroom will allow newly applied their skills to be incorporated into a daily workflow.
  • Ensure training partners have real world experience from industry – the ability to showcase relevant examples and not just the theory, can really help bring a programme to life. In our experience, the ability to share and provide value via real-world applications, combined with practical, proven approaches and best practice advice, is key.
  • Choose courses as an integral part of a leaning pathway – courses for individuals and teams should be chosen as part of learning pathways to fill any capability gaps. Processes which invest in capability, with ongoing development of skills are proven to help staff retention. There should also be processes in place to retest these new skills.
  • Demystifying data science – the ability to establish a common language between all functions of an organisation is essential to a collaborative partnership. This depth of understanding will then ensure a close alignment between analytics and strategy, supporting any barriers to change.

Following the delivery of a recent training programme delivered to AstraZeneca, Gabriella Rustici-Data Science Learning Director, commented:

“Having worked with Mango previously on a training project, we reached out to them as a trusted partner to assist us with a data science training initiative which involved helping cohorts from our R&D data science function embark on their R journey.  We were also looking for a workshop to help our scientists ‘demystify’ data science and understand the terminology – establishing a common language between scientists and data scientists.

Mango helped us create a remote virtual classroom R training program, which included support surgeries designed to enable participants to really absorb what they had learnt from the program. Feedback received from course participants was excellent, with comments such as: “ The instructor was great, really patient”, “The instructor was very enthusiastic, clearly knew their topic and the learning material was great”, “ I got a lot from the course” and “I’m keen to learn more R, hopefully with Mango”. The workshop was well received and has certainly given us a good start to increasing awareness of what data science can do.”

About Mango Training

Whether you’re seeking R training courses, Python training courses or more, our comprehensive training programmes are specially designed to guide practising data scientists and data engineers from breakthrough to mastery level in R programming, Python, Shiny, AI/ML and more.