Every computer application must have a method of storing, managing and using data. This requires an application and at least one database that can communicate with each other. Managing this connection can be difficult, especially with multiple databases. Fortunately, there are platforms that can manage databases and connections applications more efficiently. Heroku offers a Postgres management system for creating, managing, and using databases.

Organizations are losing out on data-driven decision-making opportunities when data stays in the data warehouse. While business intelligence solutions can surface insights from these data sets, it often reaches team members too late to be used for daily business operations. Reverse ETL empowers organizations to increase the value of their data warehouses through operationalization. Learn how this can transform the way companies use data and insights.

Have you been wanting to migrate your Heroku Postgres data to NetSuite but don’t know where to begin? We’ve put together a guide that will help make your migration seamless and included some tips to make the migration as smooth as possible.

Let's get started with this great debate. First, a step back; we’ve pointed out that Apache Spark and Hadoop MapReduce are two different Big Data beasts. The former is a high-performance in-memory data-processing framework, and the latter is a mature batch-processing platform for the petabyte scale. We also know that Apache Hive and HBase are two very different tools with similar functions. Hive is a SQL-like engine that runs MapReduce jobs, while HBase is a NoSQL key/value database on Hadoop.

The growth of corporate data and the need for more corporate applications and systems are not trends that will soon slow down. Data has become an essential component of commercial success and a measure of the value of a company. Investing in platforms, processes, and people that can effectively protect, transform, and leverage data is the hallmark of a modern data-driven enterprise.

Moving data from an organization’s systems into data warehouses and data lakes are essential to fuel business intelligence and analytics tools. These insights guide businesses into making decisions backed by data, allowing them to choose actions that have the best chance of positive growth. However, getting data from the source systems to these data stores can be a harrowing process.

The four key things to know about the difference between a data engineer and a software engineer are...

According to Forbes , 95% of companies need to manage unstructured data and use it to gain actionable insights. Data processing is the way to do just that. Unfortunately, poor data management occurs when companies don't make full use of the information they collect.

Modern business requires a range of digital components to communicate effectively when transferring data and delivering critical messages. Application programming interfaces, or APIs, are sets of rules that regulate exactly how certain apps or machines connect. If you work with data at all, you’ll have heard of REST or RESTful, and REST APIs — but what is REST API design? We explain below.

According to TechTarget , data governance is managing the integrity, security, availability, and usability of data in an organization's system. Effective and efficient data governance makes sure data is accurate and consistent. There are several predictions regarding data governance you need to know.