Riding the Next Big Trend in Big Data

Business Riding the Next Big Trend in Big Data Database Analysis Development

Harnessing the tactical insight of real-time data streams is the next big data trend on the horizon, and enterprises are gearing up to hop on board.

But many are drowning under the oppressive weight of legacy data management platforms and antiquated analytics approaches according to a recent study by IDC on 502 enterprises around the globe.

Using traditional ETL methods requires an average of five to seven days to migrate data from the warehouse to analytical databases, and enterprises are acutely aware of the negative impact of untimely data on their ability to make the most of business opportunities.

Transformational models of the last decade have stressed strategic decision making based on predictive insight gained from historical and landscape data. Despite this emphasis across enterprises on big data trend analytics projects, Gartner’s research discovered that only one in ten succeeds based on lack of in house skills.

Problems arise in areas such as data management and consolidation, data quality, and issues running modern analytics on technology developed in the 1970s.

Organizations are mired in data collection without the ability to get on top of ever-growing data sets, watching business opportunity pass by and crash on the shore. Controlling the strategic direction of the enterprise has focused on hindsight, reaction, and corrective measures rather than real-time agile responses to a live environment.

Day to day business is driven by line and field staff making tactical decisions in real-time to increase efficiency and open up new opportunities and requires the ability to run queries on data retrieved from local servers, outside IoT sources, and social network feeds. Building scalable systems to effectively deal with this infinite amount of structured and unstructured information requires intensive investment in top system engineers and data scientists and analysts.

Datatron simplifies this investment through a scalable and customizable platform that allows enterprises to run queries on landscape and real time data for optimum insight to inform your business as it is happening.

Our platform lies on top of your existing environment, accessing your historical data through a single interface, while simultaneously streaming and cleansing live data automatically. This allows data analysts and business users to focus on analysis and not data movement, accessed at speeds unattainable through traditional ETL methods.

Speed your innovation and increase your agility through the ability to predict incoming waves based on your historical

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