Globally, Business Intelligence (BI) is becoming a critical factor for differentiation as it empowers businesses with actionable insights to accelerate innovation and growth. The keyword here is “actionable”. Today’s decision makers have no time to spend on analysing massive data sets or sifting through charts or trend reports.
Instead, they want to get from “data-to-insight-to-next steps” as quickly as possible. Time-to-Insight has become a critical metric for data engineering teams and that is what business users are looking for.
Riding on the popular wave of digital transformation, the demand for business intelligence is being spurred by increased cloud adoption, and greater access to data from internal and external sources. As a result, the market for BI
The business benefits of BI are clear:
- Insights gathered from analytics are driving revenue growth
- Data is at the core of cost-cutting and streamlining operations
- BI is being used to differentiate and innovate get the edge on competitors
- It is no longer about qualitative customer satisfaction. Companies want measurable outcomes to prove customer delight is being delivered!
We reached out to one of our colleagues in Merit’s data engineering team to explain the BI tech stack and here’s what he said: “The modern data stack is all about making life easier for business users. Data engineering teams are making it seamless for the end-user to capture insights. At the risk of oversimplifying this – let me explain what lies under the hood. It includes data pipeline tools to centralise data from multiple sources, ETL tools for data transformation so it becomes useful for analytics, data management tools to ensure data integrity, security, and governance, a proven data warehouse and/or data lake for storage, BI to garner intelligence and finally data visualisation tools to present data to the end user.”
Key Elements of a Modern BI Stack
In 2022, every enterprise wanting to leverage business intelligence for growth should have some of the following solutions in the BI technology stack:
- Data Mesh: To become data-driven, enterprises need a centralised data platform that facilitates distributed ownership of data for easy discoverability. As an architectural paradigm, the data mesh empowers business users across the organisation with access to data and insights.
A Merit expert adds, “Data democratisation is at the heart of Modern BI. Decision-makers across levels want to have access to real-time, actionable insights. Analytics are not only for senior executives. It is about empowering the entire organisation to become data driven.”
- The right tools to present Metrics: Businesses need a way to measure success and ensure that their strategies are progressing in the planned direction. Modern BI tools must make it easy for organisations to track and monitor key performance indicators (KPIs) and metrics. Once the metrics are decided, they must be setup in such a way that a notification must go out when the company is lagging behind on a particular metric.
Airbnb’s Minerva, LinkedIn’s Unified Metrics Platform, Uber’s uMetric, and Spotify’s metrics catalog all serve this purpose.
- Extract, Load and Transform (ELT) Tools: The traditional ETL (Extract, Transform, Load) enabled populating data warehouses by pulling data from third-party systems, cleaning it up, and then loading it. However, as the need for real-time data increased, this process became a hurdle due to being time-consuming. It is being fast replaced by ELT–Extract, Load, Transform–allowing raw data to be stored in data lakes and transformed based on need.
- Active Meta Data: A fast-emerging solution layer, data catalogs are being built around different types of data assets, with active metadata for end-to-end data visibility and enabling collaboration. Active metadata platforms help to eliminate data silos. One of the biggest challenges with traditional data intelligence platforms is siloed access to insights. By embracing a modern BI tool with active meta data layers, it is now possible to truly unify data across the organisation – without compromising on governance and security.
- Visualization and Data Storytelling: Business users need the data to be presented in a form that helps them understand trends and outliers quickly. Visualisation is becoming as important as the data itself, with graphs and charts getting supplemented by data storytelling.
- AI for Predictive Insights: Faster and error-free data preparation is being made possible by integrating artificial intelligence to automate the process and minimise human intervention. This will continue to play a key role in the BI stack to improve BI and analytics capabilities, enabling predictive and prescriptive analytics.
Merit Data and Technology’s expertise in Modern BI
Merit Data & Technology partner with some of the world’s leading B2B intelligence companies within the publishing, automotive, healthcare and retail industries. Our data and engineering teams work closely with our clients to build data products and business intelligence tools that optimise business for growth.
Our data engineers can help you with faster time-to-insights by helping your organisation choose the right data pipeline and data movement architecture, based on your specific business needs.
Our data experts consult closely with our clients’ CIOs and technology decision-makers to design the data pipeline architecture that will be support budgets, project timelines and other specific requirements.
If you’d like to learn more about our service offerings or speak to a data science expert, please contact us here: https://www.meritdata-tech.com/contact-us
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