Harnessing the power of accurate data, application performance analytics and reporting tools can rapidly enable organisations to truly observe their performance. Business Intelligence can allow an organisation to make operational changes and improvements based on actual data and the experienced team at Balance Internet can help you achieve this goal.

Our Team

Balance Internet’s Data Analytics Centre of Excellence is a professional team of consultants and developers who will provide you with all the needed assistance to make the most out of your investment in the Microsoft Power BI or Tableau Software platform .

Our main goal is to help you transform organisational data into meaningful data and business results which lead to smarter decision making. We have extensive experience in organisational implementations of Power BI and Tableau, the creation of next-generation reports and dashboards, complex data modeling, advanced customisations and visualisations.

Our Solutions

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Our Power BI and Tableau consulting service is based on over 20+ years of experience in data analytics and integration. We define your BI strategy, architect and implement all the needed infrastructure, and turn your data into comprehensive and flexible dashboards to empower decision making.

Our qualified and certified Data Analytic’s consulting team delivers high quality and results that drive innovation and empower decision makers with business-critical insights. Our consulting services to help your organisation to:

  • Adopt and implement Microsoft Power BI or Tableau Software
  • Customise your BI platform to your maximum benefit and ROI
  • Integrate any data sources and maintain data infrastructure
  • Generate business value through data analytics and visualisation

Our Proven Approach

Balance Internet Data Analytics Process

Discovery & Understanding your organisational needs

Understanding your organisational objectives is vital to drive innovative outcomes that are relevant and meaningful to your environment. This knowledge drives what outputs your business is seeking and adds context to the analytical approach and methodology we will use to deliver intelligent and robust solutions that work for you.

Analysis and Gaining Insight

Gaining insight and context to your challenges, system gaps and recommending improvements will lay the foundation for selecting and defining the most appropriate analytic and pragmatic approach. This allows us to solve these problems within your business environment and context.

Data Collection

The next step after defining the analytical approach and data requirements, is to identify and gather the relevant data resources. This data may exist in a structured, unstructured or semi-structured format within your organisation. As part of this process, gaps in knowledge and systems are typically encountered, at which point the data requirements are revised and additional requirements are sought to close this gap.

Data Interpretation

Using descriptive statistics and visualisation techniques our team will start to gain insights into the data collected, assess it and prepare it for the next stage of modelling.

Data Preparation and Modelling

During this phase all data is cleaned, collected, combined, sanitised, transformed and prepared for modelling. The data collected will also be restructured and re-engineered to produce variables that enrich and enhance the model. While this can be time and resource intensive, our focus in this phase is to intelligently manage the data resources so that they are integrated correctly, and analytically clean.

With the first version of data, the team will then develop descriptive or predictive models using historical data as a training set . These models are rigorously tested, scrutinised and the data preparation and model specification refined.

Solution Deployment

Once the model has been evaluated and tested, our team will package this for approval to release. It will then be deployed into the test or production environments for initial evaluation to limit and control the release to minimise impact. If the model needs to be deployed into the operational environment, several groups and technologies may be introduced to evaluate the models efficiency and effectiveness.

Evaluation and Feedback

Mining the results from the deployed model will bring further opportunities for evaluation, reiteration and improvement. The feedback received reports on the model’s performance and its impact upon the environment it is deployed within. The observations and refinement of the model provides an opportunity for improvement and efficiency. This continuous cycle ensures that outcomes are beneficial, relevant and with context to your organisation..

Requirements Management

The data, functional and non-functional requirements that are necessary for the project will be elicited and managed over the full analysis and implementation cycle.

This is guided by standards, processes, domain knowledge, data content formats and representations existing within the enterprise.

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