In the digital age, the saying "knowledge is power" has evolved into "data is power". But harnessing this power is not as simple as it sounds. It requires a robust analytics infrastructure that can collect, store, analyze and transform data into actionable intelligence.
Understanding the Analytics Infrastructure
Analytics infrastructure refers to a combination of hardware, software and services that collect, integrate, manage and analyse data. It is the backbone that supports all your data-related requirements and initiatives. This infrastructure enables companies to track performance, identify trends, predict outcomes and make informed decisions based on intelligence.
Data Pools or Data Warehouses?
One of the initial steps in building an analytics infrastructure is deciding where and in what format your data will reside. The two main options are Data Lakes and Data Warehouses and they serve different purposes.
A Data Lake is a large repository that stores raw data in its original form until needed. It is like a huge lake filled with various data elements that come from many sources and are unstructured.
On the other hand, a Data Warehouse is a structured repository for data that has been cleansed, categorized and is ready for analysis. Think of it like a bottled water facility where water (data) is purified, tested and packaged for consumption.
So which choice should you make? It depends on your needs. If your focus is on flexibility, real data processing and machine learning, a Data Lake may be the best choice. If you need structured, reliable data for complex queries and business intelligence (BI), a Data Warehouse is usually the best way to go. In fact, many companies choose a hybrid model, using a Data Lake to store raw data and a Data Warehouse to analyze structured data.
Selecting a BI software
When it comes to selecting BI software, there is no one solution that fits all. It's important to understand your company's requirements and choose a tool that fits your needs. Important factors in your choice include ease of use, customizability, pricing, support, and the ability to handle large amounts of data.
Outsourcing or in-house development?
The choice between developing an analytics system in-house or outsourcing the process to a specialist company is another decision to be made. Outsourcing often offers significant benefits even though it may seem like it will be a challenge for you.
As data analytics experts, we have the expertise, technology and tools necessary to build an effective Analytics infrastructure. Conversely, in-house development can require a significant investment in time, resources and training, which can be a distraction from your core business.
By outsourcing the development of your analytics infrastructure, you can focus on leveraging your data while we take care of the management and maintenance.