Big Data Services

Next Pathway's Big Data Services

With the proliferation of large amounts of data, comes the growing importance of managing information from creation through to retirement – the entire lifecycle. We can help to assess critical decisions in how to store, secure, monitor and improve the quality of information.

Our Big Data Services include:

The purpose of a Reference Architecture (RA) is to develop a robust architectural framework upon which to build detailed level design artefacts. A Big Data Reference Architecture captures and conveys the architecturally significant elements that concern the design and development of an Enterprise Data Lake (EDL) platform. These requirements are unique to each enterprise; however, our RA is based on industry standards and best practices developed by Next Pathway over numerous implementations of EDLs.

These artefacts include, but are not limited to:

  • Conceptual Architecture
  • Logical Architecture
  • Technology Architecture
  • Security Architecture
The storage of vast amounts of information surrounding your customers and business requires considerable attention to security. Both for the sake of the organization and its customers. Access controls are essential to protect data lake services and resources. The advent of Big Data requires more careful attention and implications to existing information security practices.

Next Pathway has defined an access control security framework that can leverage existing access provisioning, attestation and management processes from an enterprise. The provisioning and management processes are designed based upon data ownership according to data classification, which is defined by the enterprise security policy.

Our framework uses a single scheme to control the access on various Hadoop resources such as HDFS, Hive, and YARN. It can also flexibly support application/organization structure for data ownership and permission provisioning, Data Lake access privileges, and service privileges.

Furthermore, there are various tools and techniques to deploying Big Data. Our consultants help to evaluate our client’s requirements against security needs, and deliver recommendations relating to:

  • Authentication
  • Authorization
  • Data Rating Mapping
  • Encryption / Data Protection
Ensuring data quality and data lineage is reliant upon a metadata management practice which provides a framework for capturing and classifying data elements.

Our team is experienced in defining, establishing and implementing the foundational architectural components for Metadata Management. The architecture foundation for Metadata Management defines how producers and consumers access their data.

Our services include the following:

  • Metadata Management Reference Architecture
  • Solution Architecture for Metadata Management Framework
  • Metadata Management Governance – Centre of Excellence
Big Data Analytics unleashes the power of Big Data by identifying unique patterns and trends, creating complex reports, and recognizing correlations.

Our skills in this area provide our clients with the ability to:

  • Provision a production/consumer zone, within the EDL platform, where each consumer can leverage the platform capabilities and the EDL data sets to perform production ready reporting, modeling and analytics.
  • Provision a zone, within the EDL platform, where each consumer can leverage the platform capabilities to perform exploratory analytics and modeling on EDL data sets as well as external data.
  • Move tested models from the exploratory/sandbox zone to the production zone in a deterministic and repeatable way.
  • Leverage the platform’s distributed computing capability to perform computations on large data sets.
  • Consume unstructured data for model development and exploratory capabilities.
Governed data provides an organization with clean and trusted data, enabling it to ultimately drive towards better customer value, experience, and loyalty. Data governance also allows an organization to reduce its cost in complying with regulatory policies.

Big Data is requiring organizations to re-think roles and responsibilities as it pertains to ‘ownership’ of data versus ‘stewardship’ of data. Getting these roles right ensures that the organization can operationalize data governance policies, develop and implement data standards, plan and execute changes, monitor compliance and onboard new data sources.

The degree of accountability between Data Owners and Data Stewards is often influenced by the use of the data and how the organization views the management of information. Working with our clients, we help to define these critical roles by considering other factors such as:

  • Organization Structure
  • Business Process Integration
  • Responsibilities of IT & Business
  • Segregation based on ownership
  • Development of tools, processes, policies, procedures and templates for establishing a framework for the practice of data governance

Operationalization is a key component of overall governance. It involves the strategies and principles/processes and ongoing practices for maintaining and supporting a Big Data initiative. The right operating model will drive alignment and integration across the enterprise, which ultimately unleashes the full potential and value of Big Data. Our governance practice also includes aspects such as Performance Monitoring, Charge Back Models and establishing a Centre of Excellence (CoE) in Big Data.

Contact us to find out more.