Actionable Intelligence. Delivered.
Staggering growth and diversity of data sources make data integration (acquisition and provision) and data wrangling (preparation) a foundational necessity for businesses aiming to leverage data for analytics and achieving a single source of truth.
Integration and Wrangling:
The purpose of Integration is to create fail-safe interoperability. Whereas Wrangling, a.k.a Data Preparation is done to create usable data. Both go in tandem and are deployed at various degrees depending on the nature of the project. In Enterprise Analytics/ Data Science assignments, Wrangling becomes an essential phase in the process.
Information users are increasingly taking the responsibility for data preparation using no-code, commercial Data Wrangling platforms such as Trifacta and Paxata. But we also see numerous other instances where IT continues to own data preparation.
Data Science & Analytics:
To gather insights, develop foresight, and turn them into business-impacting decisions, organizations are investing top dollars in Data Science & Decision Science capabilities. Ability to generate real insights and act on them is a true competitive edge. Ability to achieve the same at speed and scale is what makes a high-performance business.
Analytics are now an integral part of every business leader’s decision-making arsenal. Mid to large enterprises look at Big Data Analytics/ Data Science/ Advanced analytics for growth and business economics, reducing risk, make data-driven enterprise performance decisions etc.
BI & Reporting:
Legacy BI systems don’t deliver to the ever-changing demands for business reporting and analytic views even as they ratchet up costs. We are no more surprised by instances where businesses are still grappling with reporting challenges, some of which even put them at the risk for non-compliance. There’s no business function that’s insulated from this problem; whether financial, operational, regulatory etc.
Functional limitations of legacy BI along with their high TCO ought to be the trigger for transitioning to new-age/modern self-service cloud-based BI, reporting and Analytics platforms. However, we also see many instances where extending the usefulness and life of current systems becomes an immediate need as businesses seek CapEx avoidance/ postponement.
BI, Reports & Visualization
- Architect and build enterprise-level BI solutions
- Extending the life of legacy systems through business functionality addition/ bolt-on solutions
- Efficient support and maintenance
- Phase-wise, low-risk transition to a modern environment
- User training for successful adoption
Integration & Wrangling
- We build robust integrations for enterprise level analytics initiatives and business platform implementations (Veeva, Murex, Salesforce, Adaptive Insights, Workday to name a few) leveraging home-grown IP such as accelerators, frameworks, and automation.
Data Science & Analytics
- With expertise in Big Data platforms, Text Mining, AI, ML, DL, Visualization, we build statistical, mathematical and algorithmic models for predictive and prescriptive analytics.
- We have extensively deployed these models in fraud detection, customer churn prediction, sales forecast, weather forecast, event forecasting in personal health, risk prediction, sentiment analysis.
We outline in the below table the essential dimensions of solutions implementation which ensure success, speed and ROI of integration and analytics projects.
|Key Dimensions||Integration||Data Science & Analytics|
Ingestion, transformation, monitor & alarm, dashboards and reports
Knowledge of end-purpose/ target system such as Sales forecasting, Enterprise Analytics, or a Business platform such as Veeva CRM
|Custom Solution(Built using contextually chosen tools and technologies)||
|Skills||ETL, Programmer, Data Architect/ Modeler, Product Functional||
|Speed & Control||Automation, Monitoring Dashboards and Alerts|
We help you gain real insights and foresight from your data, so can achieve a competitive advantage. Talk to our experts today.