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Leveraging the Power of Tableau and Redshift on AWS Cloud for Better Analytics

21 May
By: ClearScale

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

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Dynamic Orchestration Workflow Using Apache Airflow

07 May
By: ClearScale

Data is the undisputed ruler that drives everything from business strategy and decisions to near real-time algorithmic workflows. In a data-rich world, capturing that information and processing it is a monumental task even when a clearly thought out architectural approach is implemented. When new data sources are found that require data extraction, transformation and loading (ETL) into a data store, often that activity is done with command-line requests, scheduled cron jobs or scripts that call scripts to achieve this activity

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Collecting and Enriching Data by Leveraging Snowplow for Deep Analytics

29 Mar
By: ClearScale

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

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Leveraging the Power of AWS Athena for Large Scale Big Data Queries

02 Nov
By: ClearScale

The Challenge As an organization grows, so does the amount of data it stores, either from information it creates on its own, or from an aggregation of data from multiple sources. From a business operations perspective, trying to glean useful information from terabytes worth of data in a quick and expedient way can become challenging as the amount of data grows or if multiple, complex joins are needed. A global news organization discovered this fact several years ago as they

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Predicting Consumer Credit Behavior by Leveraging Amazon Machine Learning

20 Jan
By: ClearScale

With the ever-increasing breadth of information surrounding your customers’ demographic and financial transaction history, the amount of associated data can grow very large, very quickly. From how they use their credit cards, to what vehicles they purchase/lease and when, to how often they move, rent or buy a place to live, and even how many times they use checks over debit or credit cards, consumers’ financial transactional footprints are varied and considerable. This large volume of information can be

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