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Big Data Consulting

Big Data Consulting with Mark Kidwell and Mark Ginnebaugh of DesignMind
Big Data Consulting and Analytics Solutions

Our big data consulting team leverages modern cloud analytic technologies, including Amazon Web Services and Microsoft Azure, to develop data warehousing, advanced analytics and machine learning applications that are both powerful and cost-effective.

Our consultants have a broad range of expertise across data and system architecture, data integration, exploration and visualization, descriptive analytics, data science, predictive analytics, machine learning, and AI.

We work across a variety of use cases and industries: from data warehouse and query offload of medical billing data to advanced analytics and fraud detection for payment processing and money transfer applications. We work with organizations already using Hadoop and related tools, but we also help companies new to Big Data, identifying potential high value projects, and providing the guidance and technical expertise to make their initiatives successful. Our big data consulting services range from evaluation, optimization, to technology recommendations and strategy. 

Big Data Platforms and Tools We Use

Our consultants specialize in the following platforms:

  • Hadoop (Cloudera, Hortonworks, MapR, Qubole, and Microsoft HDInsight distributions)
  • Apache Hive and Pig
  • Apache Spark and Mahout
  • Apache HBase and Cassandra
  • Amazon Web Services (Data Pipeline, EMR, Redshift)
  • Apache Impala and SQL on Hadoop

Learn more about the big data technologies we utilize. We also collaborate with the top big data vendors, and have partnerships with Cloudera, Snowflake, MapR, Qubole, and Tableau.

Our Core Big Data Consulting Services

Use Cases and Planning
System Architecture
Data Architecture and Integration
Data Exploration and Visualization
Advanced Application Development

Use Cases and Planning
Data warehouses can’t deliver data to users quickly enough? Out of control spending on storage and data processing infrastructure? Traditional database applications not scaling? How can an Hadoop or NoSQL solution solve these problems? Figuring out where to start can be the hardest part, but it’s probably the most important step to a successful big data program. DesignMind’s use-case driven approach guides our customers from generic problem statements and fuzzy requirements to an actionable plan for delivering a next-generation big data platform.

System Architecture
Designing and building a big data platform that can scale to handle billions of transactions per day and thousands of concurrent users is no easy task. Even with the benefits that scale out systems like Apache Hadoop and Cassandra provide, a poorly planned system can quickly become a nightmare to develop against and operate at scale. Our big data consulting team has years of hands-on experience building large scale systems, and leverage DesignMind’s reusable templates for capacity planning, architecture, configuration management and monitoring to help our clients build platforms that always perform at their peak. Existing systems benefit from a comprehensive review from our experts to identify problems and recommend solutions to get them back to optimal performance.

Data Architecture and Integration
Determining the best way to ingest, process and analyze terabytes of data each day is a daunting task. The Hadoop ecosystem offers a number of tools for data integration and transformation, in addition to the plethora of ETL tool vendors offering these services. But without hands-on expertise with Hadoop and knowledge of best practice in data management, a big data platform can quickly turn into the costly, underperforming database or data warehouse it’s trying to augment. DesignMind believes that agility and performance should be the mantra for all Big Data projects. Our consultants follow a use-case driven methodology for identifying key data source systems and integration points, leverage the best technology to ingest those data, and are focused on building the highest-performance systems to process data quickly and deliver insights to users faster than ever.

Data Exploration and Visualization
Getting data into a big data analytics platform is only half the problem. Getting insights out of the system is key. While Hadoop is capable of processing vast amounts of data, knowing the right questions to ask, translating them into queries, distilling the results into visually compelling results and making it all accessible to business users can still be challenging. Through our partnerships with companies like Tableau and Platfora, DesignMind can help deliver an analytics platform built around Hadoop. For companies that have a preferred BI tool already or teams of data scientists using tools like R, SAS and KNIME, we can support integration with Hadoop to make the transition for end users easy.

Advanced Application Development
Big Data isn’t just about data integration and analytics in Hadoop. Sometimes it’s a purpose-built high volume data processing application, with custom interfaces that may be used by thousands of users. Sometimes it’s the only way to scale an application that has outgrown its existing OLTP database. Either way, DesignMind’s Big Data consulting team is ready to work for you. Using core go-to technologies including Apache HBase and Cassandra, and modern application frameworks from Cloudera and Typesafe, we can help build your next generation data application.

Big Data - Our View

DesignMind Awarded AWS Cloud Consulting Partner

Qubole Snowflake Partnership Opens Possibilities for Faster, Better Insights

Qubole – The Self Service Big Data Analytics Platform

Hortonworks Big Data Analytics

Big Data Analytics Tools We Like – Hortonworks

Choosing a Data Lake Storage System

Big Data Visualization with Tableau Online

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ClientsMore

  • Annie’s Naturals
  • Exponential Interactive
  • Jamba Juice
  • World Vision

Leadership TeamMore

Mark Ginnebaugh
Mark GinnebaughCEO
Mark Kidwell
Mark KidwellCTO
Angel Abundez
Angel AbundezVP, Solutions Architecture
Christian Renninger
Christian RenningerVP, Business Intelligence

Learn more

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