Rise of the Data Warehouse

Posted by Ricky Thomas 04 Aug 2017

Data Growth

By 2020, the entire amount of digital data produced by everyone from your content marketing team to musicians updating their fans on Instagram will be more than 40 zettabytes, which is the same as 40 trillion gigabytes.

Granted, the bulk of that data is produced by machines and bots, collected by sensors and moved through smart systems. As you can imagine, this makes breaking down data and finding actionable information from it a huge challenge. An estimate from IDC reports that almost a third of data has valuable information in it that could be used effectively, if we could only access and extract it efficiently.

The Data Struggle

Unfortunately, according to Forrester Research, most companies don't take advantage of their opportunity to convert data into actionable insight. Even though almost 75 percent of companies want to be data driven, only 29 percent are efficient at converting data into better decision-making.

One of the challenges is that data spread throughout multiple systems and servers is hard to collect into one area to make it easier to manage. There are inefficient pipelines, varied systems, differing skill levels of IT practitioners and a plethora of disparate resources throughout the organization.
Furthermore, it is not cheap to store data as it entails upfront capital expenditures and other outlays. Not to mention the traditional delays that end users were forced to endure when they wanted to look at relevant data and analyze it. Data analysis is often resource intensive, slowing down databases and affecting the transactional operations of your organization.

But as organizations become increasingly dependent on data, and accurate data becomes a competitive advantage, fast access to data for analysis and decision-making becomes paramount, and that’s where data warehouses come in.

The Modern Data-Driven Organization

Data warehousing is increasingly popular because it offers advantages that on-site storage and compute resources cannot match. Companies are becoming more data-driven every day. Top managers and organizational leaders require deep analysis about every factor of the business and how it will help meet revenue goals. With the speed of business today, they can't wait for an IT technician to provide data for them from the data warehouse so they can begin their analysis.

 

One of the drawbacks of traditional data warehouses is they were not designed for the massive data sets we see today. They required upfront investment and are difficult to expand based on demand.

In contrast, a cloud data warehouse is accessed quickly and provides the requisite power to begin breaking down data into useful, actionable information. Cloud data warehouses are built specifically for analyzing huge data sets, collecting your data in a single location, and makes it instantly available to everyone in your firm. They can operate across multiple servers and nodes and leverage improvements on the fly.

Now your end-users can gain insight from every data point you have in your organization without impacting the workload speed of transactions and without the cost of traditional warehouse expenditures.

What Is Data Warehouse as a Service?

With data warehousing as a service, you don't have to worry about setting up and managing related to a data warehouse. All you have to do is add your data and pay for the service. The service provider handles all management and administration, so you don't have to hire staff to maintain your own data warehouse.

Additionally, you don't have to spend money in the beginning to build out your data warehouse and take time configuring and maintaining it. With data warehouse as a service, you're also free of the burden of updating software, and the services are available anywhere you can access an Internet connection. DWaaS allows you to grow your company based on informed analytics, tapping into the power of your extensive data sets quickly and efficiently on-demand.

Data Warehouse Versus DWaaS

What's the difference between a traditional data warehouse and a data warehouse as a service? Data warehouses typically use a relational database based on SQL, optimized for rapid queries and fast load times. In contrast, DWaaS is a cloud-based service accessed over the web. Customers don't have to set up in the infrastructure, worry about administration and can pay for the resources they use either on a subscription basis or based on volume.
The benefit of a DWaaS is data that can be loaded faster, it provides more elasticity, access is easier, data analysis is faster and it handles big data stores with ease.

Data Warehousing on the Rise

Why has data warehousing as a service grown so fast in popularity? The key is that, in today's business world, every great enterprise has excellent data management, storage, access and throughput. Unless an organization can organize data and extract value from it quickly to make lightning fast business decisions, they will be left behind in today's highly competitive marketplace.

Data warehousing has been handled in the past by large IT companies such as Oracle. As companies become more comfortable using cloud-based services, it was inevitable that data warehousing would be offered by independent providers as a service. Many are only a few years old and have expanded rapidly to meet the rising demand.

 

Benefits of Data Warehousing

  • Immediate Value Added- Cloud data warehouses provide scalable solutions with fast analytics requiring no management on your part. Self-service data extraction and analysis become simple, easy and fast.

  • Retain your Skillsets- You don't have to retrain personnel in new frameworks or languages. Users can utilize their current skills and tool sets. All they need to do is log on and begin breaking down numbers for their individual usages.

  • Consolidated Databases- Legacy data banks and semi structured data are a thing of the past with data warehouses capable of optimising your storage.

  • Fast Growth- There is almost no set up and they can be up and running in 24 hours.

  • No More Limitations- modern data warehouses provide the security, encryption, configuration and management at a reasonable cost

  • System Continuity- The system is never offline so data can be accessed at all times. In the past, losing several nodes in a system meant that the whole system and its data might be lost but now a group of nodes may be lost and the system will automatically replicate across servers, so nothing is lost.

  • Round the Clock Queries- Queries can be run around the clock, from around the globe.

  • Changing Workloads- In the past when you increased workloads, it became unsustainable, most traditional warehouses would fail. DWaaS can not only increase the availability to handle a higher workload, but can build separate warehouses to redistribute the workload.

If you have unique amounts of data but cannot access it and pull out information that will help you operate your business better, it is just like you didn't have the data in the first place.

Data warehouse as a service allows you to quickly and easily access that data from anywhere you have an Internet connection.

Topics: Data Warehouse as a Service Data Analytics Data Warehouse Database

Sign up for our newsletter

Top Posts