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Applications of Big Data

Here are some of the most common applications we’ve seen of Big Data Solutions.

Customer Relationship

Most organizations keep information on their customers spread across a number different disparate systems: CRM, CRMfinancial, point-of-sale, marketing, customer support, and so on. Imagine the questions that could be asked if all of those disparate data sources could be combined into a single, 360-degree view of each customer. For example, if a customer support person receives a customer call and could immediately tell where you were most recently looking on the company’s website, they’d be able to more effectively guide the conversation. A retail salesperson can offer more compelling products and promotions if he or she can tell which email promotions you’ve responded to mot recently. We make it easier to bring together disparate data sources — these programs can ingest data in any structure and any format.

 

Business Process Optimization

Due to a heavy dependence on disparate data management systems, many business processes today involve data movement, duplication, and processing to get unstructured data into a structured format or to make it accesbusinessprocesssible to different users within the organization.

We help companies optimize their business processes by eliminating extraneous data movement and simplifying the approach to data management. Complex logic and algorithms can be applied to data processing pipelines to automate decisions. Users across all business units can access their multi-structured data in the same place. There’s no limit to the total data volume or to the types of data that can be captured.

Data Processing / ETL

Data processing is critical to supporting organizations’ everyday operations such as generating reports for suppliers and customers, measuring internal metrics day to day and reporting quarterly financial results. Hadoop is rapidly becoming a mainstay in organizations due to its flexibility, scalability and low cost of storing and processing raw data. With an increased focus on improving operational efficiency, leading organizations across industries are moving mission-critical data processing and historical data storage to big data solutions. This enables them to store raw data in its native format and develop and maintain complex data pipelines faster, and at significantly lower costs, than were possible using traditional systems.

Data Warehouse

Hadoop took the database management industry by storm through its revolutionary ability to process massive data volumes quickly and at low cost. But organizations with intensive analytic performance demands still needed a data warehouse in place for speed-of-thought analytics — until now.

Time Series Analysis

Time series data is distinct from other data sets due to its temporal order. Traditionally, relational databases have been used as a general purpose tool to store sample time series data sets, increment counters, and to run analysis on those sample data sets. They are relatively easy to use but face challenges scaling from a storage, performance and cost perspective. Time series data is natural big data use case: machine-generated data is steadily flowing into the data Timemanagement platform and should be stored in its raw form. Our Big Data Solutions offers an ability to capture, store and analyze granular time-series data at massive scale and lower cost.