BI & Analytics Consulting

Your databases, your servers, your apps, your metrics. The full devops stack.

Service Highlights

24x7x365 Monitoring, Emergency Response & Support
Frontline team, Account Manager, and Team of DBA's
Flexible Agreements, 5 min SLA, Fixed Cost & Blocks of Hours

We provide 24x7 monitoring and response to correct performance, availability, change requests, data migration and incident for your databases. You get the expertise, availability and best practices from a team of DBA's backed by proven infrastructure support service. Using certified experts, systems and processes, we proactively manage your database environments on an ongoing basis to help you operate efficiently, predictability & securely with less overhead.

We manage, maintain & optimize your critical Oracle systems. Our DBAs have high expertise with Oracle database technology, RAC, Exadata, ODA, Goldengate and Oracle Middleware, data migrations and patching strategies. This includes Oracle Cloud

We have years of experience in all aspects of SQL-Server databases. We have extensive knowledge of backup & recovery, restore, performance tuning high availability solutions and AAG, replication and log shipping, patching and data migrations.

Expert administration support for MySQL, Percona Server, and MariaDB with various clustered solutions. We follow industry best practices with performance and backup & recovery; scaling, high availability (HA) design to meet application requirements.

We provide architecture and design advice, project assistance, clustering, database tuning and performance optimization for your MongoDB environment. BraveSoft will provision machines, configure replica sets and sharded clusters, and upgrade your MongoDB deployment

Free yourself from the complexity of infrastructure and database management of PostgreSQL options with the benefits of a fully managed service. Patching, performance investigation and tuning, backup and recovery and slave setup will allow your Postgres to meet business goals.

We allow firms to focus on the data analysis aspects of Big Data without the necessity of managing a Hadoop environment. Hadoop deployment involves configuring, deploying and managing a Hadoop cluster. This include backup/recovery, automated upgrades, data security tools and technical support,  among others. 

Solve your complex database challenges at scale with managed databases on the cloud. We businesses of all sizes initiate, optimize and manage databases on their chosen infrastructure: Amazon Web Services (AWS), Microsoft® Azure® and Single-tenant hosting for the highest levels of performance and uptime.

Microsoft offers cloud-based database on Azure which has become a popular cloud platform for BraveSoft clients.  Through our DBAs and comprehensively monitoring solution we can manage thousands of VMs, PaaS workloads, applications and manage databases deployed on Azure. We also monitor cost & resources to track cloud costs.

Amazon offers a broad suite of cloud DBMS services. BraveSoft provides Amazon RDS support and management services including provisioning, implementation, migration and ongoing administration and monitoring support.

Contact Sales

For more information about BraveSoft services please call:

US: 877-734-2780

UK: 44-800-072-5290

Specialises in data visualisation, predictive analytics, enterprise reporting, and data engineering.

Every enterprise project begins with a broad vision. The realization of this vision takes the form of a series of incremental steps. Based on studies by The Data Warehouse Institute (TDWI), the steps that lead to a mature data warehouse strategy can be generalized as an evolution from management reporting to analytical services, with the majority of companies finding a comfort level in the middle of this evolution.

In the beginning of business intelligence projects, there is typically a large effort spent readying infrastructure and establishing development methodologies. User adoption typically begins slowly, but builds exponentially as more systems are incorporated. Word of mouth and realization of the value of the data warehouse drive interest and dependency by business and management. It is critical not to attempt goals that are overly ambitious in the early stages so that what is built will be solid and dependable, building credibility and user trust as a result.

The stages of BI development are overlapping; as the organization moves to adopt each successive stage, dependencies on the prior methods of reporting continue to exist but will eventually be replaced. The diagram below highlights the stages of evolution in typical business intelligence and data warehouse projects:

  • ‍BI Implementation & Integration

Full scale BI platform architecture, design, implementation, integration and development and business validation.

  • BI Assessment & Planning

Assess desired BI outcomes, current solution landscape, create a roadmap, selection of technology & tools, and complete proof of concepts.

Development and Discovery

All development will be implemented using commonly accepted methodologies. This will facilitate future extension of the development and greatly ease maintenance and support. It is important to note that data warehouse and BI development is very much “software development” and projects should be managed in much the same way as traditional software development projects. In general, data warehouse and BI development follow an iterative approach. The iterations can be shortened to facilitate a more agile approach, but there are no shortcuts to get from a standing start to a fully populated data warehouse.

  • Discovery: Understand the organization’s current-state architecture, reporting needs per department its business processes, various data sources with its back-end logic and current silo reporting efforts.
  • Defined Data Model: Working within the scope of the targeted business case and information, along with related dimensions, define a logical representation (Semantic layer) of the data to be utilized for the presentation layer (Reporting) for each business process (Subject Area) for a given business area.
  • Data Analysis: Working within the scope, perform detailed data analysis and validation of the existing reporting efforts including their back-end logic to create equivalent structure in the new platform.
  • Data Ingestion Processes: Work with source data extract and transform the data via ETL. Provide for a fully functional and automated data transfer process will be used for data ingestion to load the data from source to target.
  • Presentation Layer: Develop dashboards, pixel perfect reports (PDFs, Excel and PPT output) to demonstrate the ability to analyze the information. Reporting will be managed in a hybrid manner per the various delivery options to meet internal reporting needs.
  • Documentation: Provide the organization with a BI solution architecture and a design document which describes the solution per data mart design and build.
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