“ Technical Assistance for Strengthening of the MARD's capacity (including policy analysis and evaluation system) ” Reference: AL-MARD-521807-CS-QCBS The World Bank is assisting the Government of Alb…

Tender summary

REQUEST FOR EXPRESSIONS OF INTEREST (REOI) (CONSULTING SERVICES) Firms Selection Climate Resilience and Agriculture Development Project in Albania Project ID Number : P178715 IBRD Loan Number : 94890 Assignment Title: “ Technical Assistance for Strengthening of the MARD's capacity (including policy analysis and evaluation system) ” Reference: AL-MARD-521807-CS-QCBS The World Bank is assisting the Government of Albania (GoA) with the financing of the Climate Resilience and Agriculture Development project (CRAD). This project aims to increase competitiveness and climate resilience of priority agri-food value chains focusing on (i) promoting climate smart and resilient value chains, (ii) promoting typical products and value addition (iii) developing Climate Smart Agriculture (CSA) IT Platform (iv) modernizing selected irrigation and drainage schemes for high-value agricultural production (v) enhancing compliance with food safety and quality standards and (vi) strengthening evidence-based decision making for resilience and sustainable agri-food systems. The services required to be contracted aim to support the Ministry of Agriculture and Rural Development (MARD) in ensuring successful implementation of the contract “Technical Assistance for Strengthening of the MARD's capacity (including policy analysis and evaluation system)”. The MoARD seeks the Consulting Services of a qualified consulting firm/consortium with the objective to assist MoARD with the Technical Assistance for Strengthening of the MARD's capacity (including policy analysis and evaluation system). The Consultant will be responsible for providing qualified professional and supporting staff and all necessary services required for the efficient cost effective and timely execution of the Consultancy Services. Scope of Work The Climate Resilience and Agriculture Development (CRAD) Project foresees the implementation of an integrated, on-premises Business Intelligence (BI) and Data Warehouse (DWH) platform to support evidence-based decision-making in the agricultural and rural development sector. The platform will centralize the collection, integration, analysis and visualization of agricultural, environmental, financial and rural development data, serving a wide range of users including decision-makers, analysts, program managers, field officers and external stakeholders such as EU institutions and development partners. The BI platform is conceived as a multi-layer, Microsoft-based architecture comprising: multiple source systems (operational databases, files, external datasets and APIs) a data ingestion and ETL layer a centralized enterprise Data Warehouse with subject-area data marts and staging areas a semantic / data modelling layer an analytics and reporting layer. The database backbone is Microsoft SQL Server using advanced features such as column store indexes, table partitioning, materialized views and high availability / disaster recovery options to handle large-scale, historical and current data in fact–dimension schemas optimized for analytical queries. On top of the DWH, the solution uses Power BI technologies to provide both standardized and self-service analytics. An on-premises Power BI Report Server will host interactive dashboards and paginated reports with unlimited internal users, while a set of Power BI Pro cloud licenses enables collaboration, sharing and modern self-service analytics scenarios where appropriate. Users will access rich, interactive visualizations (charts, KPIs, maps, matrices, trend lines), with support for drill-down/drill-through, cross-highlighting, conditional formatting, bookmarks and export to common formats (Excel, CSV, PDF, images). The platform is designed to connect to a broad spectrum of internal and external data sources-including relational databases, Excel/CSV files, XML/JSON feeds and web APIs-combining imported (cached) datasets with Direct Query/real-time access where needed. Comprehensive data transformation and p

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