The success of your big data project is only as good as the data it uses. But if you continue to have your data siloed, even if very large amounts, flaws will show up in the results, diminishing the impact of your artificial intelligence and machine learning efforts.
We can help you further leverage your existing investments by integrating your on-premise data with the ever-increasing amount of unstructured content and third-party data to maximize and produce better business outcomes.
The objective is to not only identify issues or opportunities, but also and primarily, to be able to take action from the results of the deployed advanced analytics.
Big data engineers lay the big data analytics groundwork. Data scientists then use this groundwork to create algorithms for AI models.
Your current structured data can certainly be useful, so it should not be overlooked to modernizing your legacy EDW to fit current technological standards, getting a performance and security boost along with that endeavor. Data lakes will then nourish your data-driven efforts. Then as a final step to process all of your data, both structured and unstructured, you’ll want to leverage big data technologies such as Hadoop, Spark TensorFlow, Keras and Kafka to process data streams in real time.