Imagine being able to aggregate data from different departments to generate reports only a day before the monthly meeting. Or, Marketing and Production both agree on an emerging trend, and thus, cooperate to timely respond to market change. This has been the reality for many businesses with data warehouses.

What is data warehouse?

A data warehouse is a centralized digital storage system – a vast, organized library of your company’s data history. Not only that, it also optimizes the data so that all your departments can do swift and comprehensive analytics and reporting.

Benefits of a data warehouse

A data warehouse can act as your company’s single source of truth. No more inconsistent data across departments, no more cumbersome databases, no more time-consuming reporting or slow decision making.

what is data warehouse
A data warehouse is your company’s single source of truth

Here are the benefits of a data warehouse.

Efficient reporting and analytics

A data warehouse first centralizes all data from various sources into one unified location. Then, the ETL (Extract – Transform – Load) process transforms data into a consistent format, making the data uniform. This process also cleans and validates data before it is loaded into the data warehouse. Then, data is structured by columnar storage, designed for Online Analytical Processing – OLAP. Data marts (subsets of data warehouses) can be created to cater to specific business units or functions.

Such functionality enables businesses to:

  • Compare and analyze uniform, clean, reliable data.
  • Make faster queries, especially for complex analytical queries.
  • Different departments can quickly generate specialized reporting.
  • Integrate seamlessly with modern business intelligence tools.

Historical data analysis for trend spotting

Data warehouses have a time-oriented structure. They are designed to accumulate and retain historical data over extended periods of time. Each piece of data is associated with a particular point or period in time. Snapshots are taken at regular intervals, creating a timeline of business operations.

Such functionality allows analysts to do:

  • Compare data from different timeframes.
  • Trace changes, developments, and anomalies.
  • Observe patterns as they emerge and evolve, even those spanning multiple departments, or multiple levels (from high level to granular data).

A unified view of business operations

The above functionalities removes the guesswork out of your business operation. You can ask for departmental specialized reports with uniform data over extended time frames. You can expect to have those reports in much shorter time, with higher quality. Clarity and efficiency are the values of having a data warehouse.

Improved decision-making capabilities

Modern data warehouses support near real-time data processing, so that you can have real-time insights whenever you need it. This is especially crucial during a crisis that requires fast responses.

The dimensional modeling in data warehouses allows users to “slice and dice” data across various dimensions (e.g., time, product, region). This multifaceted view of data offers deeper insights and a broader understanding.

Data warehouses often come with strong security and governance mechanisms, ensuring that sensitive data is protected. As a decision maker, you can trust the integrity and confidentiality of the information you base your decisions on.

The problems a data warehouse can solve

Let’s consider these ‘before and after’ scenarios to illustrate the benefits of a data warehouse:

Scenario 1: a data warehouse unifies disparate, inconsistent data across retail locations

A retail business has stores in multiple locations, each with its own point-of-sale (POS) system, inventory management software, and customer loyalty program.

Before:

Monthly, the regional managers scramble to compile data from these disparate systems to generate reports, often leading to inconsistencies in stock levels, sales figures, and customer purchase histories. The marketing team struggles to target campaigns effectively because they lack a unified view of customer behaviors across all stores. Critical business decisions, like determining stock reorders or launching promotions, are often made on outdated or incomplete data, leading to stock overages or shortages and missed sales opportunities.

After:

With a data warehouse, the retail business consolidates data from all its stores into one unified system. This allows:

  • Consistent, real-time reporting, eliminating previous discrepancies in sales and inventory data.
  • Marketing campaigns that are more targeted, leveraging unified customer purchase histories across all stores.
  • Proactive stock management, with real-time insights preventing overstocking or stockouts.

Scenario 2: a data warehouse can enable better management of resources and staffing for hospitals

A healthcare group operates several clinics across the country. Each hospital has its own patient management system, billing software, and electronic medical record (EMR) system.

Before:

The headquarter finds it difficult to gauge overall performance, as consolidating patient satisfaction scores, billing efficiency, and medical outcomes is a cumbersome and manual process. Further, trends like seasonal illness outbreaks or equipment usage rates across all facilities are nearly impossible to detect. Consequently, resource allocation, such as staffing or equipment purchasing, is often based on guesses rather than real-time data, leading to inefficiencies and decreased patient care quality.

After:

By implementing a data warehouse, the healthcare group manages to pull data from each of its hospitals into a unified platform. The benefits include:

  • A holistic view of patient care metrics across all facilities, so they can improve the quality and consistency of services.
  • Easier detection of patterns, such as recurrent seasonal illnesses, so that their staff won’t be overworked and under-equipped.
  • Streamlined billing and claims processing thanks to consistent financial data, so their cash flow is better managed and they have less billing errors.
  • Ability to assess and compare the performance of different facilities, so they can share best practice and implement operational improvements.

Scenario 3: a data warehouse can enable a school district administration to make district-wide improvements

A school district that oversees multiple schools ranging from elementary to high school, struggles to monitor and analyze student performance cohesively. Each school uses different grading software, attendance trackers, and extracurricular activity logs.

Before:

The district’s central administration wants to implement district-wide improvements but finds it challenging to identify patterns like drop-out rates, subject-specific performance, or the impact of extracurricular involvement on academic achievement. This disjointed data infrastructure hinders the decision-making process, potentially leading to misallocated resources and missed opportunities to support at-risk students.

After:

With a data warehouse, the school district aggregates data from all its schools into one comprehensive system. The transformation yields the following results:

  • A unified view of student performance across the entire district, allowing them to identify students in need of additional support or resources.
  • Insight into trends, such as how attendance correlates with academic performance, or which subjects across the district might be consistently underperforming.
  • Streamlined reporting for district-wide initiatives, grants, or state requirements, reducing administrative burdens.
  • Ability to evaluate the effectiveness of new educational programs or curricula by analyzing pre- and post-implementation data.

Common challenges of a data warehouse

Moving your data to a data warehouse is a complex project that requires investment and resources. You need to factor in these potential issues:

  • Performance: Real-time or near real-time processing capacity, query speed and accuracy.
  • Data security and compliance regulations
  • Scaling up – how much data growth can you anticipate?
  • The current quality of your data. Dirty, unreliable, and inconsistent data requires careful planning to ensure accurate integration.
Moving your data to a data warehouse is a complex project that requires investment and resources.

Save resources by setting up a AWS data warehouse with RenovaCloud

A data warehouse is a worthwhile investment that has proven its ROI for many businesses willing to take the leap. You may want to start with the easy step – setting up a data warehouse on AWS Redshift – Amazon data warehouse service. As a certified AWS consulting partner, RenovaCloud knows the ins and outs of AWS data warehouse, and we wholeheartedly believe in the benefits that a data warehouse can bring to a business. Contact us for our Data Platform and Analytics service and let us help you mine the richness of your data.