Most decision-makers struggle with "decision paralysis" because they have insufficient data, lack the proper tools required to gain insight into the data they do have and struggle with data fluency — the knowledge required to understand and use data to make effective decisions.

In today's data-driven world, obtaining data is no longer an issue. In fact, most businesses are drowning in it. But to make effective decisions, businesses need easy access to organized, high-quality data.

Storing data in multiple databases on separate platforms is no longer an adequate solution, as it makes maintaining data accuracy and accessibility too much of a challenge. Fortunately, data warehouses enable organizations to easily store, manage and analyze data to make intelligent business decisions quickly.

What is a data warehouse?

A data warehouse is a centralized system that combines data from various sources within an organization stored in structured, unstructured or semi-structured formats. It provides a unified view of all data pertaining to customers, business transactions, income, expenses and more.

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As part of a business intelligence strategy, data warehouses are used for data and market analytics, business reporting and decision-making. Data can be stored in a cloud data warehouse, on-premise data warehouse or hybrid solutions.

Types of data warehouses with examples

While there are many types of data warehouses used for various purposes, they're usually structured in one of the following formats:

• Virtual data warehouse: Separate databases that form a virtual data warehouse but can be queried together.
• Enterprise data warehouse: Big data warehouses that combine data from multiple sources spread throughout an organization.
• Data mart: A data mart is a small data warehouse used to analyze and report on specific aspects of a business (e.g. departmental data). 

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A data warehouse for a retail business may combine data from in-store sales, website purchases and customer information. Retail businesses can use the information stored in their data warehouse to analyze and adjust pricing policies, identify popular products and study customer buying trends.

A healthcare data warehouse, on the other hand, may combine patient information, financial transactions and insurance data. It can be used to forecast outcomes, share data with insurance providers and inform purchasing decisions.

6 benefits of data warehouses

Sixty percent of business decision-makers say they experience "decision paralysis" due to various issues with data. The benefits of using a data warehouse resolve many of those issues.

While the specific benefits of any data warehouse will depend entirely upon the business, there are six general benefits most businesses can expect to receive.

Let’s take a look.

1. Improve business intelligence and efficiency

Many businesses generate massive amounts of data from multiple sources (such as pricing, customer information, purchasing trends, vendor information and more). The sheer amount of information can be overwhelming and render it all unusable. Storing this data on multiple platforms is costly.

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A data warehouse solves this problem by bringing order to the chaos. It stores and organizes data in a centralized repository in a way that businesses can identify and extract the potential benefits through appropriate business intelligence solutions. 

Data warehouses make it easier for business users to:

• Obtain global insights: Organizations can get a global view of all of their data from multiple sources in one easy-to-view location.
• Create reports: Organizations can run complex queries of data in a data warehouse to obtain information about specific aspects of their business quickly. And with data consolidated and sanitized in one central repository, it's easier for business analysts to create reports that conform to reporting requirements.
• Collaborate: With an easy-to-access source of consistent data, different departments within an organization can collaborate effectively.
• Inform business decisions: According to a McKinsey Global Survey, 37 percent of respondents believe their organizations make quick, high-quality decisions. By making data easier to access, organize and process, data warehouses enable businesses to increase the quality and velocity of their decisions.

Data warehouses also enable businesses to reduce the cost of data management by consolidating data into one location rather than managing it across different platforms and paying multiple vendors.

2. Save time and enhance decision-making speed

Effective decision-making often involves input from different people within an organization — such as data analysts, marketing teams, management and more — and different data sources.

In the past, decision-makers would have to cross-check multiple data banks across multiple platforms, often requiring help from tech support to do so. Simply gathering this data together would be a time-wasting, labor-intensive process.

But data warehouses consolidate data from multiple sources into one convenient repository, making business-critical information readily available. When businesses need to make quick, effective decisions, all relevant parties can easily access the necessary data in one location.

With the help of AI-powered algorithms, many organizations can easily and quickly identify valuable business trends and intelligence that help them make profitable business decisions.

3. Improve data quality management

Modern businesses generate data at a rapid speed. Data must be maintained to ensure that it's current, accurate and in the format required by analytics platforms. Managing data quality can be time-consuming, particularly if the data is spread across different platforms. But combining data into a data warehouse solution makes data cleansing easy and cost-effective.

You can compare data from multiple sources, remove inaccurate or duplicated data and ensure that your data is reliable and consistent. And most data warehouse tools include sanitization techniques that automate the process and eliminate the need for costly data quality management programs.

4. Increase data security

In the face of advanced cybersecurity threats, securing business-critical data has become a difficult challenge for all modern businesses. But especially so for some businesses with sensitive or proprietary data, such as banks and pharmaceutical companies.

Storing data in one centralized location makes it easier to protect rather than having to monitor and manage multiple data banks and platforms. Many data warehouse tools include features that improve data security within and without a business. Users can create user groups limiting permissions and data access for certain people/departments within an organization.

Data warehouses often implement encryption techniques that protect data at-rest and in-flight. Some solutions also use security tactics to protect from external threats — such as the "slave read only" setup, which blocks malicious SQL code. Using a data warehouse makes it easier to store and categorize data properly.

5. Increase return on investment (ROI)

The average customer who uses Oracle ADW (Autonomous Data Warehouse) achieves an ROI of 417 percent within five years. This is due to many of the benefits, including those already discussed, such as:

• Enhanced quality and reliability of data, enabling more precise and profitable decision-making.
• Easier to access pertinent data, increasing efficiency and collaboration within organizations.
• Easier data security, enabling businesses to reduce the cost of data security efforts.
• More efficient reporting, IT staff and development.
• Reduced cost of operations by optimizing the use of resources and IT infrastructure.
• Increased revenue from more effective and efficient business operations.

6. Maintain historical data for long-term insight

While it's important for businesses to capitalize on short-term trends, they shouldn't dictate a business's long-term strategy. Businesses need long-term insight to have long-term viability. And data warehouses enable businesses to store massive amounts of data over long periods of time.

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This enables businesses to study both long-term and periodic trends to make more accurate predictions about the future and improve ROI. Historical data can be used for:

• Regression analysis: Regression analysis studies relationships between dependent variables (e.g., product sales) and independent variables (e.g., interest rates). Identifying the long-term relationship between such variables can help businesses make profitable decisions in the future. For example, businesses can study the relationship between economic indicators (such as interest rates, employment data, etc.) and customer spending to price their products throughout economic cycles effectively.
• Forecasting: Using long-term historical trends and regression analysis, organizations can make more accurate predictions about business performance (such as business growth over the next quarter).
• Discovering other trends: Historical data also enables businesses to make informed decisions, discover cause-and-effect patterns, identify market needs and discover opportunities to enhance business growth. The more data they have over a longer period of time, the more accurate their predictions and decisions will be.

Improve your data management with a data warehouse

Data warehouses provide organizations with a centralized location to store, access, manage and protect business-critical data. Companies can leverage data warehouses to:

• Quickly analyze data for various business applications
• Improve decision-making speed and efficiency
• Maintain the accuracy and reliability of data
• Reduce costs related to data storage and management
• Track long-term trends for better forecasting

For your business to remain competitive in this fast-paced digital era, you must take advantage of the features and benefits of data warehousing. Fivetran can help you load and consolidate all of your data into your data warehouse quickly and easily.

Our data connectors enable you to effortlessly centralize your data in one location. They support rapid integration between your sources and destinations, so your team can access accurate data and make faster decisions.

With log-based change data capture (CDC), Fivetran can immediately identify changes made to data in a database and replicate those changes in near real-time — delivering data as frequently as five minutes (depending upon data volume).