by Brian E. Thomas

The data warehouse in 2018

Opinion
Jan 02, 2018
Data WarehousingIT StrategyTechnology Industry

ELT has moved to the forefront and now quickly becoming the standard in big data systems.

cloud data warehouse
Credit: Thinkstock

We truly live in an age where newer technology grows almost faster than we can keep pace, yet still not fast enough for the insatiable appetite of the consumer. Additionally, business leaders want more information at their fingertips to make decisions now, and predictive analytics to be their crystal ball of information so they can stay one step ahead of their customers.

So how does a company keep pace with trends, technology and most importantly the competition? An industry peer of mine, Ronald van Loon, writes about the future of data warehousing. Specifically, he talks about deploying a new kind of data warehousing that needs to support newer BI deployments to keep up with customer demand. The main factors that drive development and deployment of new data warehouses are being agile, leveraging the cloud and the next generation of data (as it relates to real-time data, streaming data and data from IoT devices).

You may ask, “OK, great – but how do I get a hold of and implement these newer, agile data processing methods?”  That is a great question.  More importantly, if you need to focus on your business objectives and their performance outcomes, try and find an expert that not only implements and executes, but agile enough to navigate the changing data landscape and staying current in new technology.  This is where the value is realized and truly provides that competitive advantage.

Sure, there are some great platforms to buy off the shelf, or establish a partnership with an ETL (Extract, Transform and Load) provider.  However, if you go with the latter option, why not build a partnership with an expert that has a proven track record of leveraging the latest technology and ETL processes?  There are many out there, but to provide an example of this, we can look at a more modern process to ETL, which is ELT (Extract, Load and Transform).

As most ETL developers will tell you, traditional ETL can be an expensive, labor-intensive and troublesome process. When it comes to big data, leveraging the latest technology or processes is the key to efficiency. You might ask, “How is this accomplished?” Simply stated, data transformation is moved to the end in the traditional ETL process, which is considered the modern standard now.  So instead of having the data extracted, transformed, and loaded directly into the data warehouse, in the case of ELT, once the data is extracted it is directly ingested. Later, it is then transformed on read.

ELT has moved to the forefront and now quickly becoming the standard in big data systems.  This latest ETL model allows users to write their transformations in the code of choice and embody the transformations by exhibiting the number of views. The big advantage of this process is its flexibility via a quick code change on the view versus making significant changes to your transformation process.

In Panoply’s article on the evolution and benefits of the data warehouse, they state:

The incredible pace of change in the data center today is making systems management challenging in new ways. Cloud computing has created new paradigms that align with other trends like Big Data, Virtualization or Security.”

Simply put, let the proven ETL experts guide you through these challenges, and provide the right solution that best fits your organization.

Bringing together all your disparate data into a central repository or data warehouse resolves the constant issue of analyzing separate data and translating it into actionable information you can use. Data warehousing is the most efficient way that allows you to process large amounts of complex data. By implementing a data warehouse system, you will reap the benefits associated with this practice.

Many businesses today are benefiting from the common practice of data warehousing. Below is an example of the methods to improve profitability, efficiency and the overall success via data warehousing and ETL:

  • Quicker access to data
  • Better query and system performance
  • Improved business intelligence
  • Above average return on investment
  • Superior quality and consistency

At the end of the day, you must adapt to the changing technology and demand of your customers. Specifically, focus on being agile, have a cloud adoption strategy and partner with an industry ETL expert that knows innovative data processes as well as you know your business objectives.