Big Data

Data generated by household, wearables and industrial devices is growing exponentially, but almost all of it sits in separate silos and is rarely mined for insights. The real value is in unifying big data analytics to understand patterns of behavior, interaction and failure modes. This is critical to understanding how devices and services are operating, understanding the flow of communication that could constitute security threats, and weaving together dependencies and interdependent failure modes. Using Hadoop as a data lake to store Internet of Things data is a required first step, and a range of analytical approaches follow.

Outsoft is one of the few Big Data computing service providers with a cadre of experienced Big Data software developers accessible on demand to help Big Data solution providers test their hypotheses programmatically and deliver on the potential of Big Data. Our experience with data warehousing, analytics ecosystems and strong focus on data science allows us to help you evaluate and implement big data solutions for customers with diverse business processes and needs.

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Big Data Collection

The Internet of Things (IoT) is accelerating the growth in enterprise data, providing more real-time data, but also posing data management issues. The sheer amount of data flow that connected devices are capable of generating can be optimized by pre-processing the raw data into aggregated reports that are analyzed within the central database, as opposed to the process where all raw data is gathered and saved for further analysis centrally. Outsoft’s edge analytics team can help in establishing processes that treat the raw data collection more intelligently, reducing the data load on analytics servers by up to 90%.

Big Data Processing

Big data is typically highly fragmented, voluminous, “noisy” and distributed. Making sense out of big data systems requires an entirely different approach as compared to structured data management: this is where the use of tools and approaches like distributed processing, clustered file system, NoSQL distributed storage come in.

Engage with our experts to develop data intelligence systems that feature Artificial Intelligence with supervised / unsupervised / active learning, algorithm adaptation and prediction. We use Hadoop 1/2 (HDFS, Sqoop, Flume, MR, Pig, Hive, Impala, Mahout) to aggregate data for graphical data representation (with GWT, JSF, various JavaScript frameworks), data-collection, storage, processing and analytics.

Big Data Warehousing

Outsoft doesn’t sell access to own big data warehousing capabilities, but our big data team’s experience allows us to offer tailored consulting service that will weigh all the relevant pros and cons of big data warehousing solutions. In some cases traditional data warehouses can be augmented with big data capabilities, while in other cases a seamless integration between different data management systems may not be practical. The skill sets of our Big Data Team cover consulting on installation, deployment, providing production support of Hadoop clusters, can plan and implement a SQL to Hadoop migration, as well as provide Hadoop customization for existing or new components. Regardless of the scenario we guarantee an outcome that is economical yet which achieves or surpasses the set business goals.

Big Data Analysis

By 2017, more than 20% of customer-facing analytic deployments will provide product tracking information leveraging the IoT. Meeting the rising customer demand for more information from their vendors requires a rapid rethink of the enterprise value chain with scenarios where sensors embedded into all types of products play an important role. By providing this key differentiator to our customers’ business model Outsoft’s Big Data Team sees it as its mission to provide opportunities to improve transparency and strengthen customer and partner relationships. Feel free to contact us to learn how we can help curate, manage and leverage big data from your diverse sources, data from partners, suppliers, customers and open data sources.

Big Data Science

Constructing the relevant mathematical models requires both in-depth knowledge of scientific methodology and hands-on experience with business challenges specific to each industry vertical. This is why Outsoft provides direct access to big data technology architects and business domain experts to build the data analysis models. This is the approach capable of designing and extracting actionable insights from vast amounts of flowing data, or “data lakes”.

Big Data Collection

Big Data Processing

Big Data Warehousing

Big Data Analysis

Big Data Science

Why Choose Outsoft for Big Data Projects

Where the promise of Big Data lies is in providing context for decision making based on that real-time data. Big Data solutions for enterprises and individuals are already improving data-based algorithmic and semi-algorithmic decision making in marketing, transportation, financial, manufacturing and healthcare while other business verticals are still on the cusp of transformation.

Contact Outsoft about making your data more valuable and actionable for a bold, new future-proof architecture for your business today.

Internet of things

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