Access to industry-related data and information can double the effectiveness of your business in no time. Find the best business opportunities by a matter of minutes using collected data, increase your business productivity without even hiring additional people, and beat your competitors via access to the best deals. Leverage data mining, data analysis, and decision-making algorithms and their capabilities.
We identify available data sources and prepare algorithms to collect the data and save it into unstructured Data Lake for further analysis. When this is done you have a huge amount of data that will help you to find new business opportunities.
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Enormous amounts of data can't be effectively analyzed without additional preparation. We migrate unstructured data from the previous step into a structured ready-for-analysis Data Warehouse. And we deploy operational databases for real-time access for some portions of the data.
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We set up tools like Tableau to access prepared during stage #2 data. Data analytics and business owners can access available data in form of hourly and daily reports. Reports help to find useful patterns in the data and decide how the next decisions can be made.
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Decision-making algorithms start to process the data based on patterns found by analysts during the previous stage. The amounts of data, that would've been processed by a team of analytics in a couple of months, is processed by algorithms in a couple of hours or days and give you an opportunity to react on business events faster than your competitors.
Learn MoreCustom highly performant server-side software solutions to collect data from available data sources.
Cloud-based Hadoop solutions fueled by Spark processing power: Amazon EMR and Azure HDInsight.
Cloud-based Data Warehouse solutions with SQL interface: Amazon Redshift and Azure Synapse.
Real-time operations on a subset of the data: MongoDB, HBase, in some cases popular RDBMS solutions.
We build, train, and deploy machine learning models with Amazon SageMaker and Azure Machine Learning Studio.
Work with Big Data requires enormous amounts of computing power and classic database solutions just can't handle such loads. While it's possible to deploy a cluster of servers to handle Big Data operations on-premises, in most cases it is faster, much easier, and more effective to use cloud solutions from Amazon or Microsoft.
