Data Engineering, Big Data and Augmented Data Analytics
Data Engineering, Big Data and Augmented Data Analytics
In a data driven world, it is imperative that you are able to make use of the data available to your business by analyzing it and taking action on it. Data is also an asset for any company.
Generally, the data is huge, complex and unstructured. This makes it difficult to interpret it in a correct manner and often delays key business decisions in a fast-paced business world. Also, only a few companies recognize the value of the data assets and are able to monetize this. Companies like Facebook, Google, and Netflix mainly rely on their data assets to engineer new products, improve current products, and create better ways of providing value to their customers.
It is a tricky process managing the data in the right way as you need to know what and how much data you need to analyze, store and what data needs to be discarded. In absence of information on this, you may end up incurring high costs on data management itself.
Our team of experts have worked and delivered multiple data engineering projects and solutions to our clients from varied industries enabling them to leverage their data, monetize it and also take informed business decisions at the right time while keeping all of this secured.
We can help you:
Leverage real-time or near real-time data collection and analyze it
Make it simple to handle high data volumes and high velocity
Use Augmented data analytics (Machine Learning and NLP) to process qualitative and quantitative data to generate actionable insights and also enhance data quality
Develop analytic insights on voluminous data to identify business opportunities
Provide the capability to harness predictive analytics
Evaluate and identify the right tools, technological stacks and providers
Building big data solutions, deploy and monitor the assets in production environment
Create data lakes and data pipelines from internal, external data and heterogeneous data sources
Create data lakes to aggregate high volume IoT data
Create data warehouses, data marts for business metrics
Drive insights from the raw data that is engineered to a structured form
Perform cloud data migrations from your legacy data systems
Look at opportunities to monetize your data assets
Whether you are looking for an on-premise solution or a cloud hosted one, we can handle both. Our team of solution experts will build a road-map with milestones for success for you, identify KPIs and deliver to plan for a predictable success.
Generally, the data is huge, complex and unstructured. This makes it difficult to interpret it in a correct manner and often delays key business decisions in a fast-paced business world. Also, only a few companies recognize the value of the data assets and are able to monetize this. Companies like Facebook, Google, and Netflix mainly rely on their data assets to engineer new products, improve current products, and create better ways of providing value to their customers.
It is a tricky process managing the data in the right way as you need to know what and how much data you need to analyze, store and what data needs to be discarded. In absence of information on this, you may end up incurring high costs on data management itself.
Our team of experts have worked and delivered multiple data engineering projects and solutions to our clients from varied industries enabling them to leverage their data, monetize it and also take informed business decisions at the right time while keeping all of this secured.
We can help you:
Leverage real-time or near real-time data collection and analyze it
Make it simple to handle high data volumes and high velocity
Use Augmented data analytics (Machine Learning and NLP) to process qualitative and quantitative data to generate actionable insights and also enhance data quality
Develop analytic insights on voluminous data to identify business opportunities
Provide the capability to harness predictive analytics
Evaluate and identify the right tools, technological stacks and providers
Building big data solutions, deploy and monitor the assets in production environment
Create data lakes and data pipelines from internal, external data and heterogeneous data sources
Create data lakes to aggregate high volume IoT data
Create data warehouses, data marts for business metrics
Drive insights from the raw data that is engineered to a structured form
Perform cloud data migrations from your legacy data systems
Look at opportunities to monetize your data assets
Whether you are looking for an on-premise solution or a cloud hosted one, we can handle both. Our team of solution experts will build a road-map with milestones for success for you, identify KPIs and deliver to plan for a predictable success.