ClearScale Blog

The Challenge A financial analytics company's data analysis application had proved highly successful, but that success was also a problem. With a growing number of isolated data centers generating constant data streams, it was increasingly difficult to efficiently gather, store and analyze all that data. The company knew a cloud-based big data analytics infrastructure would help, specifically a data ingestion pipeline that could aggregate data streams from individual data centers into a central cloud-based data storage. Among the challenges in

For many organizations, having so much data at their fingertips can be both a blessing and a curse. While lots of data of course provides teams with valuable insights that can guide effective decision making, such an avalanche of information can also be a struggle to sift through and make sense of. Data is also ever-changing — and it’s up to teams to keep up so that they’re always gleaning the most relevant insights. The teams that stand apart

Search tools have increasingly grown power and functionality over time and both users and companies have become more reliant on them to identify information and patterns quickly and efficiently. However, even the most robust search tool can experience issues when compiling information from large sets of data. This can be due to either complex relational database joins or the sheer volume of data a single query must parse through to identify the necessary information. Every industry experiences this at some

The medical care industry has sometimes lagged behind other industries when it comes to adopting new technologies, like Big Data Analytics to make care more efficient and cost-effective. Due to the high demand for qualified specialists, the industry for years has relied on certain methodologies to help identify candidates for these types of roles which at times has been costly and not without issues. A client of ClearScale’s, an AWS Premier Consulting Partner, has attempted to solve this vexing

The Challenge Every second of every day, billions of data points are created in our online world. Making sense of all of the data and trying to find a singular piece of information that is useful, let alone actionable, is a daunting task. In the fast-moving world of news and media, being able to identify pertinent information out of all of the noise is not just important but a necessity. A large company in the global news space discovered this