Data Engineering and Data Science2018-07-08T14:49:28+00:00

Analytics are the cornerstone to how businesses perform.

Decisions can and should be supported by invaluable data insights in order to thrive in our current business climate.

Data Engineering and Data Science

For the first time in history, we have the compute power to process any size data. At Datalere, we take a DataOps approach to deploying analytics programs by incorporating accurate data, atop robust frameworks and systems. This allows us to deliver proven analytics insights quickly. Using a combination of prudent Data Engineering techniques including schema-on-read, bringing analytics processes to the data instead of moving data to the analytics processes, self-service data curation and automated discovery of characteristics/variables that accurately predict a future outcome. We effectively compress what was traditionally 80% of the effort to a fraction of that time.

Data Engineering

Data Engineering

Pick the most valuable insight, apply modern compute solutions engineered for data science, and deliver in days, not months.

  • No need to build behemoth data models.
  • No need to drop data into multiple points.
  • Update your ETL Strategy to an “Ingest and Integrate” Strategy

These are a few of our key fundamentals that help us deliver durable analytics infrastructure. Architecting your data environment and preparing the data for your data science teams allows them to spend less time on prep and more time discovering the data insights. Datalere integrates emerging agile-compute solutions for efficiencies, while utilizing our knowledge of best practices for data management.

data science

Data Science

ALL data, not just big data has valuable insights.

Advanced Analytics

It isn’t enough to just report on the past facts. Organizations should model the past as signals to predict the future while feeding contextual stimuli to enable what-if modeling. This approach support the selection of the best future course of action given the dynamic markets in which we compete.

Our data science team is equipped with the knowledge to tackle complex data solutions. As a matter of fact, we thrive on it.

Cognitive Computing

Cognitive Computing platforms encompass machine learning, reasoning, natural language processing, speech recognition and vision (object recognition), human–computer interaction, dialog and narrative generation, among other technology capabilities to provide insights to improve business outcomes the enterprise. Once the ROI is identified, we are able to rapidly deploy these projects based on an experienced team and our DataOps approach.

managed analytics

Managed Analytics

Many of our clients, large and small, have elected to outsource their delivery functions, specifically their analytics programs. This is prompted by the myriad of complex and ever-evolving technologies used to deliver these programs, along with the challenge of hiring resources. With that, we offer Datalere’s Managed Analytics Platform (D-MAP). The benefits of D-MAP include:

  • Rapid deployment using on agile delivery approach to achieve insights in days, not months.
  • Scalable and able to handle any type or size data.
  • Secure environment supported by extended teams of Security Engineers.
  • Cost effective, subscription-based for predictable budgeting.
  • Optimized delivery costs. An on-demand model allowing you to engage our Data Scientists who collaborate with your business domain subject matter experts to deliver the right solutions for your enterprise, fast.
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Digital Enteprise Solutions

Data Engineering and Data Science Training

Accelerated innovation is occuring at an exponential pace. Now more than ever, education is key to success.

Datalere’s educational programs help you stay on top of emerging solutions.

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