Big Data means big potential for organizations poised to take the next step. New tools and processes needed to realize that potential are here. Once insurmountable barriers of complexity, source, size, and structure have now been transformed into opportunities. A universe of internal, external, structured, semi-structured and unstructured data from social media, sensors, machines, web logs and other sources can now be leveraged for practical insight. Advances in speed have enabled real-time and near real-time data movement, giving greater power to analysts. Now that the answers are actually within their grasp, businesses are being empowered to ask deeper, broader, more meaningful questions.
Adastra helps clients through each step of the Big Data journey.
Big Data Planning
- Big Data Strategy: Validate your use cases, hear about new ones specific to your industry and discuss its feasibility and challenges.
- Big Data Architecture and Technology Review: Define an architecture that meets your Big Data Strategy and Objectives, and select the right tools from a dynamically changing technology landscape.
- Big Data Readiness Assessment: Before starting an actual implementation, ensure that your technologies, processes, and organization are ready.
- Big Data Test Drive. hosted Big Data environment, industry leading tools, and the support of senior consultants to help identify, fine tune, and execute a Big Data use case — a solid foundation from which to promote the value of Big Data throughout your organization.
Big Data Solutions
- Data Science Center of Competence: Establish a Data Science practice at your organization to truly leverage the potential value of your Big Data platform.
- Big Data Governance: Big Data is the Wild West. To run an effective business there, you must manage what data you allow into your system, how it is treated, and, ultimately, how you make those decisions. Data Governance is a key factor in any Big Data engagement, as it will determine your ability to manage the data into the long term.
- Big Data Quality: Implement a data quality solution, or extend your existing strategy, to ensure the insight you get from your Big Data is valid and trustworthy.
- Big Data Analytics: Mine newly acquired and variable data, as well as historical data for insight that is deeper, more meaningful, and more powerful than ever before.
Big Data Implementation
- Big Data Infrastructure: Build a platform that can respond to your Big Data needs and grow along with your organization.
- Hadoop Development: Create jobs that put your new Hadoop cluster to use, leveraging Sqoop, Flume, Pig, Hive, Spark, Storm, and other relevant Big Data technologies.
- Hadoop Conversion: Take existing processes leveraging expensive infrastructure and tools and convert them to leverage this powerful but cost effective platform.