An overlook on Datawarehousing and Business Intelligence
In this millennia, Data warehousing and Business Intelligence are big topics as of the moment. Why do you or your company need data warehousing and business intelligence and what is the output of a data processing system/process? Business data is meant for keeping. Data enables organisations to have an internal oversight and analyse each and every aspect - its customers, what it’s doing right, where it could improve, and its progression over time. The insights are far rewarding than the costs of hiring specific analysts to do the work manually. Wait, let’s go back to the tracks - how do businesses attain, organise and practically use data? The answer is through data warehousing and business intelligence.
Datawarehousing and Business Intelligence (BI). What is that?
Imagine a central repository for different informations (data). Business operations, customers data, accounting data, emails archiving, IP data, everything related to a business in one place. Data warehouses aggregate all the current and historical data that has been obtained from the many source systems used by an organisation. They are specifically set up to make analysis and querying easier. Nevertheless, to access a data warehouse, like a normal warehouse, there is security and interface of easy access layer called as well a BI platform (business intelligence platform).
Despite their differences, data warehouses and business intelligence work together. Data warehouses are frequently the core of a business intelligence platform. A data warehouse typically consists of a relational database and an ETL (Extraction, Transformation, Loading) system that enables BI capabilities.Lets get more specific on the terminology:
A relational database is a database that stores different “excel“ tables that are correlated with each other. Imagine a car seller. It has clients that buy cars that have a brand (producer) but also have specific parts (tires, breaks, etc). The information is organised into tables that can be linked based on data common to each. This makes it easier for organisations and/or analysts to better understand relationships amongst available customer data and gain new insights.
An ETL solution is usually a system or process that organisations produce to combine different data from multiple sources into a data warehouse where it will be used for business intelligence. ETL stands for Extraction - data collection process -, Transformation - data is worked out and filtered - and Loading - data is stored in a data lake / data warehouse.
On the other side of the table, we have Business intelligence (BI). Bi is a collection of technologically driven processes that take data and turn it into insights that can be used to inform and affect the strategic and tactical business choices of an organization. BI aims to address a business's known unknowns. to enable businesses and the decision-makers inside to learn things about their industry that they frequently had never even considered.
According to this research project, segregated or fragmented data is one of the most difficult components of business intelligence for 74% of top performers. In this situation, data warehousing and business intelligence work best together. A data warehouse is used to conduct searches and analyses on vast amounts of historical data. Data that is stored in a warehouse is considered to be in use because it has been transformed into the business intelligence format and processed for a specified purpose.
Some business intelligence tools draw data from source applications directly, while others need to consolidate several data sets using a data storage system. Through the usage of a data warehouse, which serves as a central location where BI applications may query and analyze data, business intelligence often combines many data sources. Although analytics and reporting tools can technically operate without data warehousing, doing so can be constrained since it is frequently difficult to connect and spot trends in data that is housed across several systems in different forms. Data is cleaned up and standardized in data warehouses, improving data quality and consistency. Processes related to corporate intelligence are streamlined as a result.
Perks of BI
Data analytics are expanded by business intelligence software beyond the fundamentals of organisational analysis. Experts in business intelligence typically distinguish between two forms of BI:
IT professionals use in-house transactional data to generate reports.
business users interact with agile, intuitive systems to analyse data more quickly.
Organisations will choose traditional BI for certain types of reporting that demand strict accuracy, like financial reporting. Modern business intelligence, however, is preferred for marketers who work in a fast-paced environment because it enables users to gain insight into dynamics, behaviours, and information that are rapidly changing, such as marketing events or campaign performance.When it comes to marketers utilising business intelligence, the common BI features we think of are dashboards and reports.
Dashboards are hosted software programs. Google analytics, or SemRush, or Power BI, or even HubSpot are pieces of software that automatically compile information into graphs and charts that show the current state of the business. They enable users to evaluate data, comprehend trends, and gain insights on current elements of an organisation, such as where sales prospects are now located in the pipeline. How many leads with a marketing qualification have we generated this month?
Reports, on the other hand, are multi-page accounts. They are used to acquire and display massive amounts of specific intelligence and are frequently in document forms. Business analysts use reports more frequently than other departments do in an organisation. Reports are a significant source of data and may be very helpful for business insights, but the information they provide isn't updated in real-time, typically only reflects one part of a firm, and can be fairly complicated and extensive, making it harder to interpret. While a dashboard can provide a variety of indicators from many departments, like sales, marketing, human resources, manufacturing, and so forth. Reports must typically be "run," which can take some time to create before being exported. However, if you need to delve further into the particulars, they are a good option.
Insights into business intelligence: useful analytics
BI features aren’t simply there for marketers to gaze at - the enticing streams of data and the highly visual dashboards - the analytics that business intelligence offers enables marketers, and organisations in general, to optimise business output and strengthen their company. Leaders that activate business intelligence insights retrieve answers to common important questions like: is my business performing well? Are my KPIs on-target, below-target, above-target or remaining static? Is the company growing and keeping returning customers?
As well as answers to those ever-present questions, BI offers a gateway to achieve different opportunities:
Better corporate strategy.
Better investment placement
Development of QMS systems
Fast scale up
Optimised ROI (return on investment)
By giving access to reports and dashboards within an organization, business intelligence can facilitate cross-departmental cooperation. Sales, marketing, and frequently other departments may track business activity and clearly identify things like where, when, and why consumers might be leaving the customer journey, where marketing qualified leads are being generated, and other things by having cross-departmental access to dashboards.
It can be problematic to practice business intelligence without a data warehouse. As we've already mentioned, data warehouses standardize and organize data, making it simpler for business intelligence (BI) software to analyze and, consequently, more useful for organizations to employ. By removing individual perspectives, data warehousing and BI solutions improve lead creation, increase efficiency, and enable firms to make decisions that are strategically relevant, resulting in a more effective organization overall.