Rick Farnell is Co-Founder and Senior Vice President, International for Think Big.
Big data dominates the headlines, yet most organizations have not figured out how to turn exponentially growing volumes of data into business value. Taking the right approach to big data, including implementing the right technologies, processes and analytics to achieve desired business outcomes, is critical.
What companies need is a strategy that blends big data and the right technology to drive business outcomes. This requires the elegant integration of technology assets and analytical capabilities such as modern data science and data engineering to get answers from big data. It’s also where most companies fall short, mostly because they don’t have the skills and expertise to apply these new big data technologies to solve new complex business problems.
Data Science Meets Data Engineering
Think Big takes a unique approach to solving the challenge of big data. Introducing Think Big
VelocityTM Services, which combine speed with direction. Implementing quickly in an agile manner is important, but it’s only advantageous if you’re heading in the right direction. Likewise, simply spending money on short cycle pilots, proof of concepts and vendor bakeoffs does not deliver business value. Technology alone provides no value. It’s what you do with data, process and technology investments that matters. We help our customers create value by combining technology with new processes and great people to achieve successful business outcomes.
Think Big Velocity Services are the result of years of experience working and consulting with global organizations, enabling businesses via emerging technology, and building a culture of big data professionals that love to come to work and deliver exceptional outcomes. We combine world-class data engineering and data science with proven IP, accelerators, and services to bring advanced analytic solutions to life. Our full range of Velocity services includes: data science, architecture, analytics operations, data engineering, training, and managed services to accelerate time-to-value and increase investment returns.
Providing End to End Services for Analytics Ops
Think Big has developed innovative technology frameworks through our production work with enterprise customers. Think Big Velocity is a proven approach to work with open source technology, yet allows for new and innovative data science methods to be applied. We started working with the Apache Hadoop ecosystem in 2010 to integrate its power to the existing data warehouse and database world, however we quickly realized that it’s about Analytics Ops or shrinking the change cycle of analytics to production that truly separates average from great.
Think Big is committed to continuously integrating the value of new open source technology and combining it together with our frameworks to bring velocity to our client’s business results. For example, one of our upcoming open-source projects, Kylo, is used by a number of global customers to solve critical problems related to production data ingestion and pipeline control across complex big data environments. Kylo integrates on-premise, cloud, and hybrid platforms with an engineering and data science control framework. In a number of our projects, Kylo has replaced the work of numerous data engineers who were hand coding ingestion services with a framework that dramatically increased the efficiency of ingesting data into our client’s big data platforms and then monitoring the data pipeline and model publishing flows. We found that our Kylo framework and investment in Apache NiFi and Spark allows corporate architecture teams to provide reusable templates to their business units to speed up the design to production cycles and increase the velocity of their business results.
Think Big, Start Smart, Scale Fast
With Think Big Velocity, companies can expect tangible returns on their investment. In a client case study, a global high-tech manufacturing firm stored data in numerous warehouse silos across several countries and in multiple systems. This prevented having a single, integrated source of data to measure quality, develop and test efficiently, and identify what was happening in their manufacturing process when things went wrong. We worked with the manufacturer to develop a roadmap, design a big data cloud architecture and select suitable big data platforms to meet their business needs. We then provided data engineering, data science, and managed services to deliver an Analytics Ops capability that allowed our customer to rapidly go from insights to production with velocity.
Within a few release cycles of using our Think Big Velocity Services methodology, disparate data sets including test, supplier, customer, and product data were brought together to gain insights into our client’s manufacturing and quality process. The flexible solution enabled real-time interactions between stakeholders, local access for anyone from anywhere at any time, and a self-service analytics portal for delivering information to users. As a result, the company saved hundreds of millions of dollars by reducing scrap, improving product testing, enhancing their traceability capabilities and improving their quality processes, while boosting customer satisfaction.