A data warehouse is a central repository where a business or organization keeps all of their digital information. Whether numerous or few, these servers host anything that could be relevant to a business such as financial data, customer data, metrics, analytics, reporting, accounting, and more. The types of systems feeding these warehouses are transactional applications or relational databases. Application input and output are analyzed by the business segment known as business intelligence, with results used to make better informed decisions for the organization in their future dealings.
Amazon Web Services takes the management of these servers and processes and offloads them to the cloud for close monitoring and easy adjustments. Your business simply agrees to the monthly AWS service charge, and you are billed according to usage of your cloud-based data warehouse. Need to decrease or increase storage space or the number of deployed redundant servers? Just tell AWS to adjust your service. In this way the cloud is treated granularly so you don’t have to pay for more than you need.
Also Read: Data Center Migration Best Practices
AWS allows for scalable data lakes that outperform traditional data warehouse modeling. A data lake houses all raw and manipulated data for the purpose of analysis. With AWS’ suite of analytic tools and machine learning, this raw formatted data can be processed for deeper insights with AWS analytics services. To make an analogy, data lakes are like the dumping ground for your data whereas the data warehouse is where polished and processed information is later stored for retrieval.
The nature of big data itself benefits greatly from the cloud computing when it comes to data analytics in the cloud. The scope of these processes involves vast stores of information, perhaps decades worth of records and reports. Let both automated and managed tools do the heavy lifting for you, parsing through the data according to your needs.
At Trianz, we will take the nitty gritty of these processes into our hands in service to our clients. First of all, migrating to the cloud is a massive chore in itself. We will be there. As soon as your company data is online, we can then run the vast array of tools at our disposal to better inform your organization’s decision making moving forward.
As a “Partner of Choice” with AWS and Salesforce, Trianz consultants are experts in leveraging cloud computing and analytics in creating measurable goals, flexible and scalable operations, faster time to value, rapid prototyping and rollout, a high degree of data availability, and a lower cost of operations overall.
Trianz can also help you achieve greater functionality and ease of use for end users, obtain a lower total cost of ownership, and promote real-time decision making and customer service satisfaction. After all, a good data warehouse stores the lifeblood of what makes your company tick—your data.
The velocity of data is something that should also be mentioned. The amount of information coming in and at such great speeds makes managing the influx a challenge. Trianz consultants will advise clients to take advantage of Hadoop-based data lakes within EDW environments, ETL processing, and a degree of analytics processing. Tightening up these processes reduces or eliminates lag time and miscommunication.
Our AWS data warehouse solutions allow richer visualization and exploration, more accurate data-based improved operations, agile development methodologies, collaboration in data curation, and more.
What you see here is a snapshot of modern data warehouse architecture. Today is a time when Big Data and its platforms are scalable, available, quick, and easy to manage with customizable and robust features regarding analytics processing for your users. Why not take advantage?
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