Understanding BIG Data
From public companies to small and medium sized businesses, every enterprise has multiple data systems that fulfils different functions. This may be your CRM, Invoicing or HR systems to name a few. These may be in big data formats, AWS or in Azure. It may be that you are unable to extract data from the cloud systems and make them talk to each other. Perhaps it just isn’t answering the questions that would aid decisions at Executive level. Our team of experts in Big Data, Analytics, Insights and Performance can help.
We access and assess your big data, how it is produced, why it is produced, and if it is answering the questions that you need to know as part of your business process. We can help to collect, clean, classify and integrate data from all these different systems through our automation service, allowing for real-time exploration of the data as a single version of truth. We make recommendations, offer solutions and then are happy to implement them. We are a flexible, experienced and based in Fleet, Hampshire with a lot of ideas on how to help you. Contact us today.
Partners and Technology
Navigating the complex landscape of software development can be challenging, especially when it comes to managing code branches effectively. With the multitude of branching strategies available, it's crucial to choose the right one that aligns with your team's needs and project requirements.
In this blog, we'll delve into the intricacies of branching strategies, focusing on three popular methodologies: Gitflow, GitHub Flow, and GitLab Flow. By comparing and exploring these approaches, we aim to provide you with insights and guidance to streamline your coding organisation and enhance your development workflow.
The customer journey is a dynamic, multi-faceted experience encompassing every touchpoint a customer has with your brand, from initial awareness to post-purchase interactions. Traditionally, businesses viewed these touchpoints as isolated events. However, the reality is far more intricate. Customers seamlessly navigate between online and offline channels, influenced by a multitude of factors like advertising, social media, and word-of-mouth recommendations. They weave a complex web of interactions, making it crucial to understand the complete picture.
So how can organisations grasp the full spectrum of the various offline and online journeys a customer undertakes before proceeding with or abandoning a purchase?
Data quality is more than just a technical concern; it’s about ensuring that the information we rely on is trustworthy and actionable. Whether it's setting long-term goals, streamlining operations, or complying with regulations, data quality forms the bedrock of successful business outcomes. In this blog we will explore the importance of assessing data quality, examining its key dimensions and methodologies for evaluation. Later using the assessment framework as the foundation, we will provide you with a step-by-step guide to building a data quality strategy.
Do you often find your organisation is overwhelmed by the sheer volume of data they possess? It is crucial not to be intimidated by this abundance. Data, on its own, holds no intrinsic value; it's the way we interpret and communicate it that drives impact. Which is why data storytelling is more than just a trend- its practise that needs investing in and it’s a skill that is assured to grow in importance. Read our blog to discover 3 key elements to get data story telling right
In an era defined by the deluge of data, the significance of data science pervades every aspect of contemporary life, offering a pathway to uncovering hidden patterns, predicting future trends, and fostering meaningful advancements across industries. In this blog, we'll delve into the key features of and methodologies within data science, its importance in today's world, and actionable advice on how to initiate your organisation’s journey into the realm of data science.
Power BI reports rely heavily on the quality and efficiency of the data they connect with. Yet, there are instances where the required data is not readily available or does not align with report requirements. In such cases, developers resort to manual adjustments, risking inefficiency and unsustainability in the long run. Power BI developers need to dedicate significant efforts to optimising this transformation process to achieve the best possible report performance. To truly leverage its capabilities, it is imperative to optimise the way you use your data.
Data chaos is not necessarily negative; rather, it refers to a shift in the organisation's data mindset that impacts people, processes, and systems. Nevertheless, navigating data chaos is inherently challenging. Establishing a solid foundation for data transformation amidst these complexities is essential for creating a successful data asset that meets the organisation's future needs.
Big data lies at the heart of making data-driven decisions. Datasets that satisfy at least three of the five V’s (Volume, Velocity, Variety, Veracity, and Value) can be characterised as Big Data. As educational institutions race to be kept abreast of technological advancements, they are inundated with big data on a day-to-day basis. Big data holds immense potential for educators, offering insights to personalise learning, identify struggling students, enhance teaching methods and improve overall educational outcomes. However, successfully implementing and benefiting from it requires careful planning and execution. This blogs explores the various opportunities and limitations of big data in the context of education sector. Furthermore, it provides clear and actionable steps to get started on your big data journey.
In today's data-driven world, agility is not just a desirable capability but a critical success factor for organisations embarking on data transformation journeys. Agile delivery methodologies offer a pragmatic and effective approach to navigating the complexities of data transformation, enabling organisations to achieve accelerated time-to-value, enhance stakeholder collaboration, drive continuous improvement, and mitigate risks effectively.
With the proliferation of data analytics solutions and consultancies, choosing the right partner to navigate this complex landscape can be a daunting task.
For many organisations, figuring out what kind of analytics solution their business needs is the first hurdle. The technical language may be unfamiliar, and the sheer breadth of possibilities can be intimidating. As a result, many businesses struggle to determine which type of analytics they truly need to address their specific challenges and drive growth.
In this blog, we will delve into the intricacies of selecting the ideal data analytics consultancy for your business. From understanding the different types of analytics to evaluating consultancy expertise and offerings, we aim to provide you with practical insights and actionable tips to guide you through the decision-making process.