Enterprise Data Warehousing Solutions: Optimize Your Business with Scalable and Secure Data Management

From social media to google ads to business websites, today’s businesses continue to generate vast amounts of valuable data across various platforms and channels. 

Every company needs some sort of repository of information about its business, a mirror to look into to reveal its past successes and failures and, in effect, inform its decision-making. 

That mirror is a data warehousing solution.

The enterprise data warehousing industry is snowballing; its worth is estimated to be $30 billion by 2028 .

But what is data warehousing, and why is it essential in today’s business landscape?

What is Data Warehousing, and why is it essential in today’s business landscape?

Investopedia defines data warehousing as a centralized system for storing historical data that can be analyzed in various ways. The data warehouse is used by businesses and other organizations to analyze historical performance and make operational improvements.

The question is, why is enterprise data warehousing critical today?

In today’s business landscape, data warehousing is vital for businesses aiming to optimize profit and reduce costs.

Data-driven enterprises need robust solutions to manage and analyze the enormous amounts of data generated across the organization. 

These solutions must be adaptable enough to support a wide range of data types and use cases and scalable, dependable, and secure enough for regulated industries. These demands are far beyond what any traditional database can handle.

This is where data warehousing comes in!

Data warehouses are a single source of truth, a containment system for effective data collection, storage, and integration.

These systems are robust enough to support various data types and use cases businesses generate.

Types of Data Warehousing:

Data warehouses are the backbone of many organizations, providing a central repository for storing and analyzing large amounts of data. 

But not all data warehouses are created equal. In fact, there are several different types of data warehouses, each with unique strengths and weaknesses.

Traditional Data warehousing

Traditional data warehousing is also known as on-prem data warehousing.

It is a data w arehousing solution located on-site, within the office space. Your business is responsible for its hardware, server rooms, etc.

They are also great for organizations with a large amount of structured data like financial transactions or customer information.

Traditional data warehousing solution is expensive since the business must continually provide the proper hardware.

It is often difficult for businesses using on-prem data warehousing solutions to scale because growth means acquiring hardware, more physical space, and more resources will be expended. 

This system is also poorly flexible as it runs on very limited computing power and may not support all use cases.

• Real-time data warehousing

This warehouse type is optimized for handling streaming data and can process and analyze data in real time. 

Real-time data warehouses are often used for monitoring and analyzing IoT devices or tracking customer behavior on e-commerce websites.

• Data mart

Next, we have the data mart. A data mart is a smaller version of a data warehouse focused on an organization’s specific department or business unit. 

Data marts often provide specific teams with access to the data they need without navigating the larger data warehouse.

These are very helpful when the organization’s data is too large to be handled by one warehouse; hence it is broken down into smaller chunks.

Cloud-based data warehousing

The foremost analyst research firm Gartner, predicts that by 2025, 80% of data warehousing will be in the cloud.

So what is a cloud-based data warehouse?

A cloud-based data warehouse is a data warehouse built to run entirely on the cloud.

This type of warehouse is built on a cloud-based platform, such as Amazon Redshift or Google BigQuery

A cloud services provider such as Amazon Web Service, Google Cloud Platform, or Microsoft Azure manages and hosts a cloud data warehouse solution. 

The cost of the services depends on your business needs, and billing could be fixed or based on usage.

Because cloud-based data warehousing doesn’t require buying any hardware, the initial investment is typically much lower, and the lead times are shorter than with traditional data warehousing solutions. 

In addition, cloud data warehouses offer the following to businesses;

• Scalability: if the business needs to scale, it is just a matter of easily paying for more storage.
• Cost-effectiveness: businesses do not have to pay for any storage that was not used, so there is no risk of overpaying for things that I wouldn’t use.
• Ease of integration with other cloud-based services: Since cloud data warehouses are already in the cloud, connecting to a range of other cloud services is simple and hassle-free.
• Reliability: cloud data warehouses are very reliable; they are always accessible because they operate as distributed systems across various countries. A failure in one doesn’t necessarily affect you.
• Security: cloud service providers have some of the best professionals in the world; they’re tasked with securing your data and implementing security systems that are almost out of this world.
• Remote friendly: Are you a company with workers distributed across the globe? Then a cloud data warehouse is a perfect solution for you.

Cloud data warehouses are perfect for companies with remote workers because they can be accessed anywhere with an internet connection.

What are some of the latest trends in enterprise data warehousing today?

It’s 2023, and many businesses realize how invaluable a data warehousing solution is. What trend should we look forward to?

Here are five trends we will see more of this year and beyond.

• Cloud-native : Many organizations are moving their data warehousing to the cloud platforms, such as Amazon Redshift, Google BigQuery, and Microsoft Azure Synapse Analytics. These cloud platforms offer scalability, cost-effectiveness, and ease of integration with other cloud-based services.

 

• Self-service analytics : An increasing number of organizations are looking to provide their business users with self-service analytics capabilities by implementing data warehousing solutions. Self-service analytics are easy to use and can be integrated with popular business intelligence tools. Low-code or no-code BI tools like Datameer have to be used for this to work. This allows for users-both technical and non-technical from various teams to interact with and work on these data.

 

• Real-time analytics : The use of streaming data and real-time analytics is becoming more widespread as organizations look to gain insights from their data as quickly as possible.

 

• Data governance : With the increasing amount of data, organizations are looking to implement data governance best practices, that include data quality, data lineage, data catalogs, and data security to ensure data consistency, accuracy, and security.” in Gartner Style.

 

Wrap-Up & Additional considerations

What if management wants to make data-driven decisions?  The enterprise data warehouse will be one of the first places they must look into.

A means to bring together both technical and non-technical members of your enterprise so that they can collaborate, transform and understand the vast amount of data in your data warehouse becomes essential for your organization.

Bridge that gap by integrating Datameer with your marketing data warehouse.

Datameer allows your team to visually explore, build, and automate data insights using SQL or No Code in one solution.

With Datameer , you bring together your team– data engineers, analytics engineers, analysts, and data scientists – on a single platform to collaboratively transform and model data for faster, error-free projects.

Try Datameer today for free.