Generic SQL (GSQL) is Lucid’s own SQL generalization utility. It enables an SQL code written in an abstracted SQL language (with GSQL specific constructs/tags that is proprietary to Lucid Dashboard Framework) is passed through a GSQL parser. This in turn will emit the target database specific SQL code (either in TSQL or PL/SQL).
This ensures that there is no impact to the performance of generated SQL code at run time as parsing is handled at design/development time . The emitted SQL code is target specific and makes use of the native features (if any) of the target DBMS.
With GSQL, a centralized version of the SQL code is maintained for each solution supporting different databases. This makes the solution extensible, i.e. to support new databases (like DB2, Netezza) by adding the required parser module (Netezza or DB2), without having to rewrite the entire solution specific SQL code targeting the new database.
Lucid Dashboard Framework
The Lucid Dashboard Framework enables quick development of fit-for-purpose dashboards, through a library of widgets that can provide actionable information in an intuitive manner.
with other portals
Requires minimal skill-set to develop and maintain
Key features of the framework
Information mash up
Mashes up internal and external data such as RSS feeds and blogs.Goal setting and tracking
Allows for metrics, goal definition, tracking and intelligent trending.Truly versatile
Deployable across OS, browsers, and webservers.Good application integration
Exposes services using REST.Highly secure
User authentication and authorization – can also be integrated with any existing LDAP. Data is secured by 128-bit encryption.
Rich library of components developed using infographics
Customized prebuilt charts and graphs
Interactive analysis for decision-making
“What if”, comparative, sensitivity analysis etc.
Collaboration for effective actions
Options for auto-notification, workflow, email.
Offers the ability to select different perspectives – for a CEO or a CFO.
Allows for user level personalization – including dashboard layout.
Quick turn around
Assembly of pre-built components means it’s instant.
Data transformation and integration
Ability to pull data from multiple types of data sources.
Provides all data transformation abilities.
Lucid Data Integration Service Accelerators
We have built our own accelerators to deliver high-quality data integration services, quicker at a lower cost. Some of our accelerators are:
Shared containers/mapplets built with reusable logic.
For example a shared container to enforce primary key, unique key, foreign key constraints for ETL against IBM Pure Data Analytics (Netezza) system is used as the product does not enforce such constraints at the DB level.
Generic ETL jobs/templates, which use runtime metadata to extract data from source and load to target.
These are multi instance jobs which can work based on user defined SQL (or table metadata) as source and run “n” instances in parallel to quickly load target. These work across different ETL toolsets as well.
Data validation routines designed to validate and report any referential integrity violations.
They function in a batch mode, especially on MPP systems (like IBM Pure Data Analytics – Netezza). Since the validations are done at non-real time, it improves the load performance and the violated records are flagged off from further processing.
Lucid Engagement Framework
To ensure every engagement with Lucid is fruitful, we follow a ‘skills integration approach’ — a multi-skilled engagement team of business analysts, technical architects and subject matter experts.
SME outlines the business problem, along with industry benchmarks, conventions and best practices.
Business analyst is the interface to business — to help articulate goals and current needs.
Technical architect — with inputs from the subject matter experts and analysts — design a technical solution that will address business problems and support business goals.
Lucid Project Management Framework
To create products which fit today’s requirements while also able to scale up to future market demands is the constant endeavor of the product engineering team at Lucid.
Our proprietary sustainable product engineering framework (SPEF) addresses the three key pillars of product engineering: Speed of development, transparent quality, continuous improvement.
This framework offers the engineering team the flexibility to innovate while ensuring consistency in the quality, along with faster development throughput.SPEF integrates best of CMMI and SCRUM practices to provide a unique methodology where control of a matured CMMI process is experienced while enjoying the high velocity of SCRUM development.While the three pillars of the framework has been integrated into the overall SPEF methods, tools and techniques, the individual engineer’s productivity and performance has been shaped based on Watts Humphrey Personal Software Process (PSP) principles.
The Sustainable Product Engineering Framework can be visualized to comprise of four distinct phases. Product Conceptualization, Product Engineering, Product Release and the Product Support phase.
Sustainable Product Engineering Framework (SPEF)
Our projects are anchored around drivers of risk management — identifying issues, risks and concerns, at every step. Risk-based decision-making through careful evaluation of decision analysis and resolution (DARS of CMMI) is an integral part of project management at Lucid.Our team is made of trained project management professionals who are well equipped in nuances of their domains. They are also experienced in product engineering where the inherent risks of product development and lean process of agile methodology are significant.
Project managers at Lucid is ably assisted by a centralized PMO and dedicated process engineers who scan the environment for early warning indicators which enable proactive issue resolution rather than problem solving.