What is a Data Warehouse – Definition, Example & Benefits

In this article, we’ll begin by sharing the data warehouse definition with examples and then explain what are the benefits of having a data warehouse for businesses. Business Intelligence (BI) may not tell you what to do about your business or what will happen if you follow a certain direction. But, it provides a way for you to analyze data to recognize trends and derive actionable insights.

However, to setup business intelligence and develop a data-driven culture, businesses must simplify access to accurate, unified, and real-time data. And this is where data warehousing comes in.

You will learn:

What is Data Warehousing
Examples of a Data Warehouse
Types of Data Warehouses
Benefits of a Data Warehouse for Organizations
How Astera Data Warehouse Builder Can Help

Table of Contents

What is Data Warehousing Definition?

To understand data warehousing, it is crucial to first understand data warehouse definition. So, let’s find out the meaning of data warehouse definition and look at a typical data warehouse architecture.

According to data warehouse definition, it is a central repository of data stored from an extensive range of sources within and beyond the enterprise. It is a technology that combines structured, unstructured, and semi-structured data from single or multiple sources in order to deliver a unified view of data to analysts and business users for improved BI. Therefore, it is used for analytical and business reporting purposes, which helps in keeping past records and analyzing data to optimize business operations.

It is also important to understand the difference between a database and a data warehouse as often people confuse the two. While a database is merely a conventional technique to store data, the latter is a type of database that’s specially intended for data analysis. It stores everything in a single location from numerous external databanks.

Data Warehouse Examples Explained

A data warehouse has numerous real-world applications in the corporate world to facilitate business decisions. Let’s look at a few examples of how they are used across various industries to understand data warehouse definition better.

In retail:

For the retail industry, a good example would be a retail data mart that incorporates customer information from cash registers, mailing lists, websites, and feedback cards. Similarly, another relevant example of the application is the healthcare sector that uses it to access the patient’s reports, share important data with insurance providers, predict outcomes, etc.

In healthcare:

In healthcare, these central stores of data are used to record patient information from different units of the medical unit. This would include patient personal information, financial transactions with the hospital, and insurance data. All this is consolidated in the data warehouse and connected through the database schema.

In construction:

Similarly, in construction, the construction firms require data of every purchase made during the construction timeline. This purchase needs to be attributed to a source to make financial decisions. The same goes for the wages of contractual employees.

All this data will be recorded in a data store and later used for business intelligence by key decision makers to estimate the overall spending of the company on a single construction site.

In finance:

Banks, insurance firms, trading firms, and others related to the finance sector need accurate data at all times. This is only possible when the data in the databases is validated properly and aptly connected with other tables in the database.

These are just some examples of how data warehouses are used widely in different industries and for varying purposes. Since they are just an organized store of raw data, they can serve many purposes for the end-user.

Types of Data Warehouses (DWH)

There are three main types of data warehouses (DWH) mainly used in enterprise systems. They are:

Enterprise Data Warehouse (EDW): As a centralized data warehouse, EDW provides a holistic approach to organizing and presenting data.
Operational Data Store (ODS): ODS is a data store suited for when neither the OLTP nor a DWH can support a business’s reporting requirements.
Data Mart: A data mart is designed for departmental data, such as sales, finance, and supply chain.

Benefits For Organizations

Now that we are aware of data warehouse meaning and how they work, it is time to know the benefits of data warehouses and how exactly they can help your business grow and scale. Whether you own a digital marketing agency or have a traditional brick-and-mortar setup, data warehousing can yield several benefits for your business.

Below are 7 key benefits of data warehousing for your business:

1. Saves Time

In the modern fast-paced world of cut-throat competition, your capacity as a business to swiftly make refined decisions is essential to outpace your opponents.

A DWH provides you access to all your required data in a matter of minutes, so you and your employees don’t have to dread an approaching deadline. All you need to do is deploy your data model to acquire data within seconds. Most warehousing solutions allow you to do that without using a complex query or machine learning.

With data warehousing, your business won’t have to rely on the 24/7 availability of a technical expert to troubleshoot problems associated with retrieving information. This way, you can save plenty of time.

2. Improves Data Quality

The refined quality of data helps guarantee that your company’s policies are based on precise information about your corporate exertions.

By understanding the data warehousing meaning, you can transform data from multiple sources into a shared arrangement. Consequently, you can ensure the reliability and quality of your corporate data. This way, you can identify and remove replicated data, poorly recorded data, and any other errors.

Implementing a data quality management program and improving data integrity can be both costly and laborious for your company. You can easily use a data warehouse to eliminate a number of these annoyances while saving money and boosting your organization’s overall efficiency.

After all, poor data quality is a burden for your business and can decline the overall efficiency of your plans.

3. Improves Business Intelligence

You can use a data warehouse to gather, assimilate, and derive data from any source and set up a process to leverage business analytics. As a result, your BI will improve by leaps and bounds, owing to the capability of effortlessly integrating data from distinct sources.

Let’s face it: cross-checking numerous databanks can be tough, and at times, inconvenient. But, with a data warehouse in place, everyone on your team can have an integrated understanding of all the relevant information in a timely manner.

An EDW allows your sales and marketing teams to track and identify which of your targets are dynamic and have accounts on social networking websites. So, if you’re running a promotion that targets females in their mid-twenties working in the beauty industry, your team can fetch profiles of your target audience using your data lake within seconds. They won’t even have to crosscheck worksheets and databanks.

4. Leads to Data Consistency

Another important benefit of using central data stores is the evenness of big data. Your business can benefit from a data storage or data mart in a similar arrangement. As data warehousing stores large amounts of data from diverse sources, such as a transactional system, in a consistent fashion, each source will generate outcomes that are synchronized with other sources.

This guarantees improved quality and consistency of data. Consequently, you and your team can feel assured that your data is correct, which will result in more cognizant corporate decisions.

5. Enhances Return on Investment (ROI)

According to a report by the International Data Corporation (IDC), using a data warehouse generates an average 5-year ROI of 112 percent with an average payback period of 1.6 years.

It empowers you to increase your overall ROI by harnessing the value and acumen implanted within numerous databanks. As you increasingly make use of the information consolidated and organized within the central store, you achieve more out of your investment.

Thus, you can elucidate, enumerate, and validate the efficiency of your initiatives to higher management in terms of improved ROI.

6. Stores Historical Data

As a data warehouse allows you to store large volumes of historical data from databases, you can easily investigate different time phases and inclinations that can be ground-breaking for your company. Thus, With the right and real-time data in your hands, you can make superior corporate decisions concerning your business strategies.

Moreover, predicting the results of your business processes is a significant aspect of being a resourceful business person. It can be challenging to forecast the future without a tangible understanding of your historical achievements and letdowns.

For example, suppose you own a fashion brand. You plan to launch a promotional campaign for your new clothing line. Setting up a central repository enables you to access and analyze historical data from your previous campaigns in order to identify which approach worked the best, and how you might emulate it in upcoming promotions.

You can’t expect to store and analyze such comprehensive past data in any conventional databank. Thus, using EDW gives you an advantage in your business procedures.

7. Increases Data Security

Did you know that complications related to data cost a large number of businesses more than a whopping five million dollars every year?

But, with data warehousing, you can save yourself from the hassle of additional data security.

As a business that deals with customer information regularly, your first and foremost priority is to protect your existing and prospective consumers’ information. Hence, to evade all future nuisances, you take all the necessary actions to escape data breaches. Using a warehousing solution, you can keep all your data sources consolidated and protected. This will significantly decrease the threat of a data breach.

A data warehouse allows improved security by offering cutting-edge safety characteristics erected into its setup. Consumer information is a valuable resource for any company. But once safety becomes a problem, this information becomes your main burden.

These are just a few advantages that data warehousing has to offer for your business. It provides you with improved business intelligence, robust decision support, superior business practices, and effective analytics processing.

How Astera Data Warehouse Builder Can Help?

It may seem like a huge investment today, but in the future, an EDW can help you reap maximum profits in terms of money, resources, and improved business performance.

Astera’s Data Warehouse Builder can help easily automate the process of building an enterprise data warehouse. It expedites

Transforming and integrating disparate data
Modeling of schema structure
Delivers an agile data warehouse
Through a unified and intuitive platform

Take advantage of this powerful product and create an agile data ecosystem today. Get in touch today or try our product Astera Data Warehouse Builder.

— Update: 08-02-2023 — cohaitungchi.com found an additional article Top 10 Benefits of Data Warehousing: Is It Right for You? from the website www.datamation.com for the keyword benefits of data warehouse.

Using a data warehouse is becoming increasingly necessary for today’s organizations, especially as many require current information for better decision-making. If you’re thinking about exploring the possibilities of data warehousing soon, these advantages can show you what to anticipate. They’ll also help you determine if a data warehouse is the best choice for your situation.

10 Benefits of Data Warehousing

1. Unlock Data-Driven Capabilities

The days of making decisions with gut instincts or educated guesses are in the past—or at least, they should be. Today’s leaders can now use recent data to determine which choices to make. A data warehouse makes that possible.

Making effective use of information means eliminating data silos and instances where single departments control most or all of the information. A data warehouse can prevent those unwanted circumstances. Then, it’s easier for the appropriate parties to source the information they need without going through other departments to get it.

A data warehouse serves as a centralized information repository. When people can go directly to one place to get the necessary information, they’ll feel more confident using it to make decisions that shape an organization’s future.

2. Maintain Data Quality and Consistency

Data could become useless to an organization if it is poor quality and shows numerous inconsistencies. However, a data warehouse can support improved quality and consistency, provided people develop a system for finding and fixing errors before transferring content to the data warehouse.

Preparing the data could mean removing duplicate records, putting all data in a standardized format, and correcting outdated data. Ensuring data warehouses contain high-quality information facilitates using those repositories to their fullest potential.

Imagine if a customer service representative could not contact customers about defective products and associated recalls because they needed the current details for those individuals. Alternatively, if a data warehouse contains a high percentage of duplicate records, it could cause a person to make the wrong decisions. Creating a quality framework for people to follow is an excellent way to make the data warehouse’s contents as valuable as possible for everyone who uses it.

3. Use Data From Numerous Sources

Most organizations don’t have all of their information in one place. It comes from various departments. The customer service team may have statistics about how many people contact them monthly about specific issues. Then, the marketing department probably has data about specific campaign outcomes and whether they fell short of or surpassed expectations.

The great thing about a data warehouse is it combines data from all of those places within the business, making it more usable for different needs. The warehouse puts that information in a consolidated format, shortening the time frame required for people to get the insights they need.

Accessing information gathered throughout an organization also minimizes the inconsistencies that can occur if people don’t have holistic data. Suppose a leader makes a decision without the benefit of information from all affected departments. Then, they may reach faulty conclusions that compromise the outcomes and impact the organization by placing it under preventable threat.

4. Realize the Power of Automation

Data warehousing allows people to experiment with how automation might improve their businesses. Automating various steps within operations is becoming more popular, especially as people realize the value of using automation to prevent costly mistakes and accelerate workflows.

A market analysis predicts global industrial automation will be worth $265 billion by 2025. That’s impressive since the 2020 worth was $175 billion. Businesspeople can rely on data warehouses to support various automation initiatives. They might use software-defined workflows to automate data access and transfer, shortening the time required to gather information for auditors, potential investors, or other parties.

People may also automate data analysis, allowing them to uncover insights faster than before. Other possibilities are to automate error detection and logging. Then, users will become aware of potential problems more quickly and know where to start in finding the root causes. A clear understanding of how an organization uses a data warehouse will highlight some of the most appropriate ways to pursue automation.

5. Respond to Business Growth

As companies grow, they often expand into new markets or serve larger customer segments. A data warehouse can contain the information people need to pinpoint the extent of a current growth period and how long it’ll last. Users can also retrieve information to study what likely caused the business’s success. Was it a new product, lower prices, or offering in-demand items at the most opportune times that made people most interested in and loyal to a company?

Business leaders frequently access location data before approving expansion options. Where does it make the most sense to open a new distribution center, convenience store, or dental practice? A company may consider offering subscription services for beauty boxes, fresh food kits, or baby essentials. A data warehouse contains the information that can pinpoint the most viable cities or communities to serve during the initial rollout.

Decision-makers may also depend on a data warehouse to learn whether now is the best time to hire new team members for specific departments or to cope with seasonal demand spikes. Although growth periods are often exciting, uncertainty characterizes them, too. A data warehouse holds the information that can make people more confident in choosing how they’ll respond to growth and how to make that success endure.

6. Get Data Warehousing on a Subscription Model

Data warehouses typically require significant investments and upfront costs. Those realities can make some executives balk at creating and using such offerings. However, the data warehousing-as-a-service model eliminates most of those obstacles. It allows people to pay for data warehouse usage through a flat fee and only to get specific desired services.

A Maximize Market Research report expects a 21.7% compound annual growth rate for the market between 2022 and 2029. The analysts said the ease of use and ability to access the data over the internet with an application programming interface (API) were some of the factors driving growth. They also pointed out how difficulties associated with the COVID-19 pandemic made more business leaders realize they needed to access current and dependable data to minimize disruptions.

Snowflake, IBM, Google, and Microsoft are some of the top companies offering data warehouses through subscription tiers. Company leaders thinking about using them should first make lists of their must-have features and ponder how such products could help them meet data warehousing goals.

7. Learn More About Your Customers

It’s becoming more common for companies to offer their customers personalized content. Doing that can increase the chances that people spend more time interacting with a service or website or cause them to spend more money on products than expected.

Personalized recommendations can become significant parts of a business model. Consider how most Netflix users decide what to watch after the service’s algorithm suggests content. If people enjoy what they consume, they’re more likely to remain subscribers and have overall good impressions of using Netflix to stay entertained.

Data is the essential ingredient of customer intelligence. What are their pain points, and how could your company ease them? Which factors make people more or less likely to complete a purchase at your site? How did customer behavior change after a recent site redesign? These are all questions a data warehouse’s content could answer.

8. Enjoy Interoperability Between Physical Solutions and the Cloud

Business leaders are embracing the cloud and realizing how convenient it is to have data stored there rather than solely using hardware in company headquarters. Some of today’s data warehouses are entirely cloud-based. Others work at least partially in the cloud, supporting company representatives yet to transition to the cloud fully.

Data warehouses provide the flexibility to work well regardless of a company’s current infrastructure and information storage practices. Thus, no matter what stage a business is in with its cloud usage, there’s a data warehousing solution to suit.

Cloud-based solutions are convenient for people who need to access data from anywhere. Such individuals could include traveling sales representatives, remote workers, and executives who want to compare company performance across multiple sites.

9. Retain the Security of Your Data

Keeping information in multiple locations makes security more challenging. Many executives don’t know how much data they have, let alone how to access it. Since a data warehouse allows storing data in one location, it raises the visibility of the information and facilitates a cybersecurity team’s plans to secure it.

It also helps that most data warehousing platforms have built-in security features. Some allow setting things up to block harmful SQL code from outsider attacks. Others restrict how much data a person can see at a time, minimizing the chances they’ll use the content for unapproved purposes.

Organizations can also specify which people can access a data warehouse’s material and why. Then, individuals only see information that directly relates to their role or task. Further, some data warehouses may lock users out if they try to access them from unusual locations, making it more difficult for online intruders to exploit weaknesses.

10. Study Historical Overviews of Business Activities

Having the most up-to-date information about a specific facet of a business is valuable, but it may only show part of the picture. People in positions of authority often need to see how an organization has changed over time. Those insights allow them to make more confident predictions about what’s on the horizon.

Fortunately, a data warehouse can contain historical information, allowing a person to obtain the necessary information through a few queries. Executives can typically get the content themselves without support from IT teams. That capability enhances productivity and keeps an organization running smoothly.

Historical data can also support preparedness for teams throughout an organization. People usually can’t predict the future with total certainty, but they often find the past holds valuable clues about what might happen soon.

3 Examples of Data Warehouse Benefits in Action

Now that you know some of the main advantages of data warehouses, you’re probably curious about how people use them in real life. These examples help answer that all-important question.

1. Compiling Data for Cancer Research

Efforts are underway to improve cancer data interoperability. Succeeding in this area could reveal new treatments or show which types of cancer respond best to certain widely utilized interventions. However, challenges arise since people often record clinical data in various unstructured formats. Thus, extracting the data for further study becomes prohibitively time-consuming.

Researchers solved this problem by creating an automatically updated data warehouse for cancer patient information. It contains material about 67,617 people with six tumor types. Results from this landmark project showed the automatic-updating feature allowed users to get the most current test results and treatment outcomes. They could then use that information to improve prognoses for current and future patients with cancer.

2. Supporting Information Sharing Between Multiple University Departments

The University of Minnesota’s motto is “Driven to Discover.” It comes as no surprise that the institution has an enterprise data warehouse that aids authorized users in answering essential questions. The data warehouse enables five of the university’s central departments to build and publish visualizations, dashboards, and analyses.

People from the university’s campuses and colleges, as well as individual students, can author data queries and build databases and visualizations. The data warehouse’s scalability makes it a future-proof platform able to meet diverse needs now and later.

3. Tracking Cost and Availability Data for Military Weapons

Virginia’s Defense Acquisition University is a U.S. Department of Defense arm that teaches military and civilian staff and federal contractors about acquisition, logistics, and technology relevant to their work. The organization created the Maintenance and Availability Data Warehouse. It stores more than 12 years of maintenance records from 46 data systems used by the military.

The massive data warehouse contains more than 1.6 billion records of maintenance and supply-related transactions in a standardized format. People use this resource to differentiate between each military weapon’s standard and unusual maintenance and availability aspects. Such specialized information supports informed planning and better national security readiness.

What Are the Disadvantages of Data Warehouses?

Time Required for Data Warehousing’s Early Stages

Many leaders must pay more attention to the time required to plan, design, and populate their data warehouses. These phases can collectively take the better part of a year. However, the time frames vary based on metrics such as the amount of information going into the warehouse, its quality level, and the number of formats.

People must set realistic expectations for their data warehousing initiatives. Otherwise, they may become prematurely discouraged and give up before seeing how data warehouses can help their organizations.

Risk of Outdated Technologies and Performance Degradation

A data warehouse is not something people can let run with little oversight after getting it established. Instead, relevant parties must ensure the system runs with up-to-date technologies and performs smoothly, even as data volumes increase.

All data warehouse projects need ongoing support and investment. When company leaders opt for on-premises solutions rather than those operating in the cloud, there’s an increased risk that the data warehouse’s infrastructure may become outdated. If that happens, people often notice progressive slowness when running queries or otherwise interacting with the system.

Possibility of Not Using the Warehouse Enough to Justify the Resources

Business leaders may find the cost-benefit analysis of data warehouses does not warrant building them. Besides the resources necessary to get the data warehouse operational, a company may also hire extra team members to prepare information for the data warehouse or oversee how things operate.

Decision-makers must verify that the planned use cases justify the implementation and upkeep expenses. If they decide against building a data warehouse, investing in an end-to-end business intelligence platform is another solution. Outlining the specific ways a company will use and benefit from a data warehouse is an excellent way to see if the associated costs make sense.

When Does an Organization Need Data Warehousing?

It’s not always easy to determine the right time to invest in a data warehouse. However, many company representatives start thinking about this option when their workflows require querying data from numerous disparate sources. That can be time-consuming, but a data warehouse typically makes it much more manageable.

Data warehouses can often improve productivity in cases where employees struggle to use data because it exists in many formats. Taking the time to clean up the data before it goes into the warehouse can make the information more usable later. That’s especially true when companies set rules for how to format new data.

Organizations become more likely to need data warehouses as their information volumes rise. Inefficient queries caused by the lack of a data warehouse aren’t significant issues when companies only work with small databases. However, as the total information reaches the petabyte scale and beyond, those slow queries could significantly disrupt business processes, necessitating using a data warehouse as soon as possible.

Deciding Whether You Need a Data Warehouse

Data warehouses can be highly beneficial, mainly as more company leaders rely on accurate information to drive their business decisions and maintain competitive advantages. However, they also require significant ongoing investments.

People tasked with exploring the benefits of data warehousing should compare those characteristics with a company’s primary goals. They should also ensure employees across the organization will use the data warehouse often enough to support its creation and upkeep.

Evaluating these aspects makes it easier to judge whether creating a data warehouse is the best option for an organization’s current and future needs. Then, people will have the knowledge needed to feel confident in their ultimate decision.

— Update: 09-02-2023 — cohaitungchi.com found an additional article 10 Benefits and Use Cases for A Data Warehouse from the website blog.panoply.io for the keyword benefits of data warehouse.

A recent IDC DataSphere forecast report predicts that the compound annual growth rate of global data creation and replication will reach 23% between 2020 and 2025.

Another study suggests global data creation will grow to over 180 zettabytes during that same period.

Cheaper data storage and advanced analytics technologies are contributing to the current data explosion. But aggregating that data into a single place where you can easily analyze it remains a complex task.

With data trapped in isolated systems across an organization, teams struggle to access accurate, consistent data from the multiple analytics and ETL tools being used.

Fortunately, organizations can use a data warehouse to collect, organize, and analyze data on demand.

The role of data warehousing

Data warehousing consolidates large amounts of data from multiple sources and optimizes it to enable analysis for improving business efficiency, making better decisions, and discovering competitive advantages.

Note that a data warehouse is not the same as a database.

While both are relational data systems, a database uses online transaction processing (OLTP) to store current transactions and enables fast access to specific transactions for ongoing business processes.

On the other hand, data warehouses store large quantities of historical data and support fast, complex queries across all data using online analytical processing (OLAP).

This article will examine the benefits of a data warehouse and offer use cases where such a system could add value to your business.

Data warehouse benefits

A successfully implemented data warehouse can help your organization in several ways. It offers:

1. Consistency

Data warehousing typically involves converting data from multiple sources and formats into one standard format, making it easier for users to analyze and share insights on the entire collection of data.

More consistent data means that individual business departments such as marketing, sales, and finance can use the same data resource for queries and reports to produce results consistent with the other departments.

2. Centrality

Most organizations need to merge data from multiple subsystems built on different platforms to perform valuable business intelligence. Data warehousing solves this problem by consolidating data into a single repository, making all the organization’s data available from a centralized location.

3. Access

Data warehousing improves end-user access to a wide range of enterprise data.

In many cases, business users and decision-makers have to log into every individual department system and manually consolidate data or request reports through IT personnel to get the data they need. Using a data warehouse, business users can generate reports and queries on their own.

Users can access all the organization’s data from one interface instead of having to log into multiple systems. Easier access to data means less time spent on data retrieval and more time on data analysis.

4. Auditability

The goal of a data warehouse is to ensure that data is accurate, current, and accessible—which is also the goal of the auditing process.

A data warehouse can ensure data integrity through implemented controls for roles and responsibilities related to extracting data from source systems and migrating to the data warehouse.

Security controls implemented within the data warehouse ensure that users only have read access to data.

5. Data sanitization

When data gets integrated from multiple systems, it can become inconsistent because of incomplete, duplicated, or redundant information. If the data is not cleansed or corrected, these errors could reflect in queries and reports, leading to inaccurate insights.

Data warehouses use a sanitization process to eliminate poor-quality information from the data repository. The method detects duplicate, corrupt, or inaccurate data sets, then replaces, modifies, or deletes records to ensure data integrity and consistency.

Use cases for a data warehouse

The following use cases demonstrate how you can use a data warehouse in your organization.

1. Marketing/sales campaign effectiveness

Marketing data can get scattered across multiple systems in an organization, including customer relationship management systems and sales systems. By the time teams pull together scattered data into spreadsheets to calculate important metrics, the data may have become outdated.

A marketing data warehouse creates a single source of data from which the marketing team can operate. In addition, you can merge data from systems within the organization and external systems such as web analytics platforms, advertising channels, and CRM platforms.

With a data warehouse, all marketers have access to the same standardized data, allowing them to execute faster, more efficient initiatives. Teams can generate more granular insights and better track performance metrics such as ROI, lead attribution, and customer acquisition costs.

Data warehouses can also process data in real-time, enabling marketers to build campaigns around the most recent data to generate more leads and business opportunities.

2. Team performance evaluations

Data warehouses can help evaluate team performance across the organization. Users can dig deeper into team data to create customized dashboards or reports, showing team performance based on specific metrics.

Metrics derived from the data warehouse, such as usage patterns, customer lifetime value, and acquisition sources, can be used to evaluate customer service, sales, and marketing teams, respectively.

In addition, combined data sets from other business areas can also highlight how teams have contributed to overall business performance and objectives.

3. IoT data integration

Internet of Things (IoT) devices, or network-connected devices like smartwatches, kitchen appliances, and security devices, generate vast amounts of data that you can analyze to improve systems and processes.

This data must be collected and stored in relational formats to support historical and real-time analysis. Then, instant queries are performed against millions of events or devices to discover real-time anomalies or predict events and trends from historical data.

IoT data analysis requires a high-performance, easy-to-access platform that’s flexible enough to respond immediately to changing conditions. This data can be summarized and filtered into fact tables with a data warehouse to create time-trended reports and other metrics.

4. Merging data from legacy systems

Legacy data is information stored in an old format or obsolete systems, making it difficult to access and process. Unfortunately, many businesses still rely on mainframe environments and other legacy application systems despite technological advancements in platforms, architectures, and tools.

One reason is that these systems have captured business knowledge and rules that are difficult to migrate to newer platforms and applications over the years. But the information within legacy systems can be a valuable data resource for analytical systems.

Legacy systems were built to perform specific functions and did not get constructed to analyze data. As a result, companies that run core functions on a mainframe or other legacy software don’t have timely access to core transactional data for real-time information.

Gaining access to data locked away within legacy systems can be pivotal to solving business problems and can help you discover trends you might not be able to see with newer data.

Data warehouses can automatically connect to legacy systems to collect and analyze data. Using ETL, data warehouses can transform data from legacy systems into a format that newer applications can use.

Merging legacy data with new applications can help provide greater insight into historical trends, leading to more accurate business decisions.

5. Analyzing large stream data

Large data streaming is a method that processes, you guessed it, large streams of real-time data to extract insights and useful trends. A continuous stream of unstructured data is analyzed before it gets stored to disk, and the value of the data can decrease if not processed immediately.

Processing occurs at high speeds across a cluster of servers in real-time; data cannot get reanalyzed once streamed.

Large stream data is continuously generated by multiple sources. The data can vary widely from a mobile device or web application log files to in-game player activity, social media information, and e-commerce purchases. Processed data gets used for several analytical purposes, such as aggregations, filtering, correlations, and sampling.

Data analysis performed on large stream data gives businesses insight into business and customer activities such as service usage, website clicks, device geolocation, and server activity.

A data warehouse can group large stream data to show its overall statistics. For example, a delivery company collects delivery event data that is sessionized to determine overall statistics for delivery times and the distance traveled.

The many benefits of using a data warehouse are evident in the above use cases, including:

Streamlined information flow
Enhanced data quality and consistency,
Improved business intelligence
Significant competitive advantage
Improved decision making

Conclusion

Organizations that capture the full benefits of data are better equipped to handle changing market conditions and evolving customer requirements. As a result, data warehousing can offer great value to businesses to centralize and create more consistent data that’s easier for business users to access.

And as you’ve seen, data warehouses can be beneficial in several business scenarios, including marketing campaigns, IoT data integrations, and analyzing large stream data.

If you have complicated data requirements, a data warehouse can make things easier. With next-generation data warehousing tools like Panoply, you can connect all your data to a central data warehouse, reducing the time needed to get the most out of your data.

— Update: 14-02-2023 — cohaitungchi.com found an additional article Top 5 Benefits of a Data Warehouse for Your Data-driven Organization from the website www.tibco.com for the keyword benefits of data warehouse.

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A data warehouse is a centralized repository that stores data from all areas of your business. The concept of data warehousing is pretty easy to understand and has long been considered the core component of business intelligence (BI). IT creates a central location and permanent storage space for the various data sources needed to support a company’s analysis, reporting, and other BI functions.

And it’s really important for your business.

But managing a data warehouse (or many warehouses) effectively also costs money—big money. The problem is when big money is involved, it’s tough to justify spending it on any project, especially when you can’t really quantify the benefits upfront. And data warehousing often requires other products to manage effectively, such as data virtualization. In fact, many companies are replacing data warehousing with frameworks like an agile data fabric. But not all companies can do this, as they’ve invested countless hours and dollars into a large-scale data warehouse.

Luckily, when combined with the cloud and virtualization capabilities, data warehousing can be effective and advantageous for your business.

5 Benefits of a Cloud-based Data Warehouse

In the cloud, modern data warehouses rely on major vendors like Snowflake, Amazon RedShift, and Google BigQuery—and you can expect this trend will continue. Compared to legacy data warehouses, cloud providers have increased performance and cost benefits that aid in business decision making. Here are the top five benefits:

Deliver Enhanced Business Intelligence

By providing data from various sources, managers and executives no longer need to make business decisions based on limited data or instinct. In addition data warehouses, and the BI they connect with, can fuel insights for marketing, finance, operations, and sales.

Save Time

Since business users can quickly access critical data from a number of sources in a single platform—they can rapidly make informed decisions on key initiatives. They won’t waste precious time retrieving data from multiple sources.

Users can query the data themselves with little or no support from IT—saving more time and money. That means business users won’t have to wait until IT gets around to generating the reports, and hardworking IT analysts can focus on keeping the business running.

Increase Data Quality and Consistency

A data warehouse implementation includes the conversion of data from numerous source systems into a common format. Since data from various departments is standardized, each department will produce results in line with all the other departments. With data virtualization capabilities, you can have more confidence in the accuracy of your data. And accurate data is the basis for strong business decisions.

Provide Historical Intelligence

A data warehouse stores large amounts of historical data so you can analyze different time periods and trends to make future predictions. Such data typically cannot be stored in a transactional database or used to generate reports from a transactional system.

Generate a High ROI

Companies that have implemented data warehouses and complementary BI systems have generated more revenue and saved more money than companies that haven’t invested in business intelligence.

Unify Your Data with TIBCO

Data virtualization complements a data warehouse. If your enterprise decides to build a data warehouse or already has one, data virtualization can act as a unified virtual layer or virtual data fabric. The data warehouse—along with any other databases, applications, APIs, master data, or other assets—will connect and use a data virtualization platform as the source of ingestion. Many organizations use data warehouses as targets for caching data virtualization extracts.

TIBCO Agile Data Fabric solutions optimize data management and integration capabilities so you can accelerate data pipelines, share data assets, and adapt your ever-changing data architecture. A modern, distributed data architecture allows you to address today’s data challenges in a unified way with several key benefits:

Faster time-to-solution
Flexibility
Simplicity
Cost-effectiveness
Consistent and secure data governance

So whether you’re looking to upgrade your current data warehouse or are deciding if a data warehouse is right for you, TIBCO is here to help.

Learn more about the benefits of data virtualization and data warehousing in this whitepaper.

This blog was originally published by TIBCO on 8/10/2011.