Consolidating multiple sources of data into one consistent, accurate, and accessible location.

Your business generates vast amounts of data every day, but if you’re not storing and organising it properly, you’re not getting the full value out of it. That’s where data warehousing and data lakes come in.

What are data warehouses, data lakes, and data lakehouses?

A data warehouse is a centralised repository of structured data that is used for reporting and data analysis. It allows organisations to store large amounts of data in a single location, and to access and analyse that data quickly and easily.

A data lake is a centralised repository of structured and unstructured data that is used for big data analytics. It allows organisations to store and process large amounts of data in a single location, and to access and analyse that data using a variety of tools and techniques.

A data lakehouse is a hybrid approach that combines the features of a data warehouse and a data lake. It allows organisations to store and process both structured and unstructured data in a single location, and to access and analyse that data using a variety of tools and techniques.

For most small-to-medium organisations, a data warehouse is the right fit. Data lakes and data lakehouses tend to fit better for large enterprises, generating volumes of data that would overwhelm most data warehousing solutions.

When data warehouses make sense for you.

There are a few common scenarios when it might be the right time to invest in a data warehouse or data lake:

1. When you have large amounts of data: If you’re dealing with large volumes of data that are difficult to manage and analyse, a data warehouse or data lake can help you store and organise your data in a centralised repository, making it easier to access and analyse.
2. When you need to integrate data from multiple sources: If you’re working with data from multiple systems or databases, a data warehouse or data lake can help you integrate and organise your data in a single location, making it easier to analyse and get insights.
3. When you need to support advanced analytics: If you’re looking to use advanced analytics tools and techniques, such as machine learning or big data analytics, a data warehouse or data lake can provide the storage and processing power you need.
4. When you need to improve decision-making: If you’re looking to improve your decision-making process by getting better insights from your data, a data warehouse or data lake can help you analyse and visualise your data in a way that makes it easier to understand and act on.

Ultimately, the decision to invest in a data warehouse or data lake will depend on your specific business needs and goals. We’ll carefully evaluate your data requirements and determine if a data warehouse or data lake is the right solution for you.

Practical examples.

Consider our friend ACME Manufacturing Inc. who, like many manufacturers, runs multiple operating systems to manage their workload.

1. The manufacturer is dealing with large volumes of data from multiple systems, such as production data, financial data, and customer data. This data is difficult to manage and analyse, and it is hindering the company’s ability to make informed decisions.
2. The manufacturer decides to invest in a data warehouse to store and organise its data in a centralised repository. The data warehouse integrates data from multiple systems and allows the company to access and analyse its data more easily.
3. The manufacturer uses the data warehouse to identify bottlenecks in its production process and optimise its operations. By analysing data on production efficiency, cost trends, and supplier performance, the company is able to reduce costs and improve efficiency.
4. The manufacturer also uses the data warehouse to identify new product opportunities and target marketing efforts. By analysing data on customer demographics, sales trends, and product performance, the company is able to identify new products and markets to pursue.
5. The manufacturer sees a significant ROI from its data warehouse investment. The company’s improved decision-making and optimisation efforts lead to increased sales, reduced costs, and improved customer satisfaction.

This is just one example, but the possibilities for using a data warehouse to drive ROI are endless. By storing and organising its data in a centralised repository, almost any type of business can gain insights and make informed decisions that drive growth and improve efficiency.

So why only see part of your picture?

We’ll help you bring together your data sources, and help you soar to new heights.