Take authority, responsibility and accountability for exploiting the value of enterprise information assets, and of the analytics used to render insights for decision making, automated decisions and augmentation of human performance.

More Uses of the Data Lakes Toolkit:

  • Achieve desired results through planning, risk management, stakeholder management, conflict resolution, governance, team management, and ownership of the cloud adoption lifecycle.
  • Recognize and drive opportunities to lead technical considerations in designing Data Lakes, Data warehouses, IT operations analytics based on Machine learning methodologies, and similar large scale Data products.
  • Formulate: exposure to the use of statistical analysis and machine learning techniques towards building intelligent and/or predictive analytics solutions.
  • Support your existing platform ingest, curation and export of data assets and identify areas for improvement in stability, resiliency, scale or speed.
  • Ensure you understand that making software do the right thing is only part of the battle you also must think about what can cause your software to fail.
  • Manage multiple resources located in different geographic locations and projects concurrently to ensure successful completion of analytic projects.
  • Develop a prioritization framework to evaluate IT projects and priorities and ensure regular communication with business stakeholders.
  • Establish and implement best engineering practices as architectural design, unit and regression testing, test driven development, pair programming, and continuous integration frameworks.
  • Be certain that your organization oversees the integration and staging of data, and the development and maintenance of the Data Lakes, data warehouse and data marts, for use by analysts throughout your organization.
  • Support product management with product feature gap analysis, competitive threats and product launch strategies derived from competitive analysis.
  • Pilot: influence customer strategy, architecture, roadmap, and migration planning workshops spanning business, applications, information, and technology domains.
  • Be certain that your organization develops and maintains controls on data quality, interoperability, and sources to effectively manage risk associated with the use of data and analytics.
  • Collaborate with and manage external technology partners to optimize technology architecture with a focus on security, performance, flexibility, cost, and maintenance.
  • Perform analytical tasks in a methodical manner on large amounts of structured and unstructured data to extract actionable business insights.
  • Take strategic direction from management and lead strategic planning activities throughout the lifetime of the project.
  • Be accountable for architecting and implementing ETL and data replication solutions that provide timely and accurate ingestion of data to data warehouses and Data Lakes.
  • Collaborate with product owners and technical directors to align priorities and approach employing agile software development methodologies.
  • Confirm your organization oversees the development of appropriate governance framework and mechanisms for the effective use of information and technology to create value, manage risk and establish prioritization.
  • Bring new development ideas to existing applications and processes, look for ways to enhance existing specifications based on current requirements.
  • Ensure you understand enterprise wide system modules and components for re use and provide requirements for specific architecture components for new development activities.
  • Ensure you understand the fundamental concepts of database design and the need for database architectural strategies to fit business or industry requirements.
  • Develop and present business cases, industry trends, competitive differentiators, in alignment with the go to market product and solution strategy.
  • Supervise the integration and staging of data, and the development and maintenance of the Data Lakes, data warehouse and data marts, for use by analysts throughout your organization.
  • Collaborate across teams to communicate product strategy to internal stakeholders, manage feedback and adjust priorities appropriately.
  • Control: team up with analysts, product managers, and other stakeholders to understand evolving business needs and translate reporting capabilities accordingly.


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