Data Analytics and BI Outsourcing

Last updated: November 11, 2026

Most companies are not short of data; they are short of reliable numbers. Sales, finance and operations each pull their own Excel files, the same KPI shows three different values in one meeting, and the monthly management pack takes days to assemble by hand. With data analytics and BI outsourcing, a 360 Soft team builds and runs your reporting layer: data integration and a data warehouse or lakehouse, agreed KPI definitions, management dashboards in Power BI, Tableau or Looker, automated reports and ad-hoc analysis, all under a clear SLA. Teams work remotely, on-site or hybrid from Istanbul and can start typically within 1–2 weeks. For other services, see all outsourcing services.

What is BI outsourcing and who is it for?

BI outsourcing means handing the design, build and day-to-day operation of your reporting and analytics to an external team that works to your priorities. It covers the full chain: connecting source systems, modelling data, defining metrics once, building dashboards, scheduling reports, monitoring data quality and answering business questions with analysis. It suits mid-sized companies without a dedicated data team, scale-ups whose reporting has outgrown spreadsheets, enterprises that need extra capacity for a migration or a new platform, and groups that want consistent reporting across subsidiaries and countries. It is also a practical option when you have one strong analyst who is overloaded with routine report requests.

Typical problems by function

Function	Typical problem	What BI changes
Management	Monthly pack built by hand, numbers disputed	One automated pack with agreed definitions
Sales	Pipeline and target tracking in spreadsheets	Live pipeline, quota and conversion dashboards
Finance	Slow close, manual P and L by unit	Automated P and L, budget vs actual, cash views
Operations / supply chain	Stock, lead times and service levels unclear	Inventory, OTIF and capacity dashboards
Marketing / e-commerce	Channel data scattered across tools	Unified funnel, CAC and cohort analysis
HR	Headcount and turnover tracked manually	Workforce, attrition and absence reporting

Scope of the service

Source system analysis: ERP, CRM, e-commerce, marketing, finance and HR tools, files and APIs
Data integration and ETL/ELT pipelines, scheduling and monitoring
Data warehouse or lakehouse modelling (star schema, semantic layer)
KPI dictionary: one documented definition per metric, with owners
Management, departmental and operational dashboards
Automated reports and subscriptions by email or Teams/Slack
Ad-hoc analysis, deep dives and presentation-ready insights
Row-level security, access management and data quality checks
Training and documentation for business users

Roles

Role	Responsibility
Data / BI analyst	Requirements, dashboards, reports, ad-hoc analysis
Data engineer	Pipelines, warehouse, data quality, performance
BI developer	Semantic models, DAX/LookML/calculations, visual design
Analytics lead	Roadmap, KPI governance, stakeholder management

Platforms: Power BI, Tableau, Looker and others

Layer	Typical tools
Visualisation	Power BI, Tableau, Looker / Looker Studio, Qlik, Metabase
Warehouse / lakehouse	Microsoft Fabric, Azure Synapse, BigQuery, Snowflake, Redshift, Databricks, PostgreSQL
Integration	Azure Data Factory, dbt, Airflow, Fivetran, SSIS, Python
Sources	SAP, Microsoft Dynamics, Logo, Netsuite, Salesforce, HubSpot, Shopify, Google Analytics

We are platform-neutral: if you already have licences, we build on them; if not, we compare options with you based on cost, skills and existing infrastructure.

Regulation and standards

Reporting often touches personal data (customers, employees) and financially sensitive figures. Our team operates under Turkey’s KVKK, and for international clients we work under GDPR, with a DPA and Standard Contractual Clauses (or the UK IDTA). Where relevant, we follow data minimisation, pseudonymisation and role-based access, and we document data lineage so that auditors can trace a number back to its source. Sector rules, such as banking or healthcare data requirements, and local regulations in your country apply in addition and are reflected in the design.

Delivery and service models

Model	How it works	Best for
Project	Fixed scope: warehouse, first dashboards, migration	Getting a reporting foundation in place
Dedicated team	Named analysts and engineers working on your backlog	Ongoing demand, evolving priorities
Managed BI service	We run pipelines, refreshes, support and change requests under SLA	Companies without internal BI staff
Capacity extension	Analysts join your existing data team	Peaks, migrations, parental leave cover

Process steps and typical timelines

Discovery (1–2 weeks): stakeholder interviews, source inventory, report inventory, KPI candidates.
Design (1–2 weeks): data model, KPI dictionary, dashboard wireframes, security concept.
First release (typically 4–8 weeks): priority pipelines and the management dashboard.
Roll-out: departmental dashboards, automated reports, user training.
Run and improve: monitoring, support, monthly backlog prioritisation.

Illustrative scenario

Illustrative scenario: a distribution company with an ERP, a CRM and an e-commerce shop prepares its monthly board pack by hand over several days. A 360 Soft team connects the three sources to a cloud warehouse, agrees definitions for revenue, gross margin and stock days with finance, and publishes a management dashboard plus a scheduled PDF pack. Analysts then handle change requests from a shared backlog. This is an example set-up, not a reported client result.

SLA and KPI table

KPI	What it measures	How targets are set
Data refresh success	Scheduled loads completed on time	Agreed per pipeline
Data freshness	Age of data in dashboards	Daily, hourly or near real-time as needed
Incident response time	Time to acknowledge a broken report	By priority level
Change request lead time	Time from request to release	By request size
Data quality checks passed	Automated tests on key tables	Defined test suite
Adoption	Active dashboard users and views	Tracked monthly

Pricing factors

Factor	Impact on cost
Number and complexity of sources	More systems mean more integration work
Data volume and freshness	Near real-time needs more engineering
Number of dashboards and users	Larger scope, more support
Platform and licences	Existing licences reduce set-up effort
Model	Project, dedicated team or managed service
Support hours	Business hours or extended coverage

Data Analytics and BI Outsourcing — overview

In-house team, freelancers or outsourcing?

Criteria	In-house	Freelancers	Outsourcing (360 Soft)
Skill mix	Hard to hire analyst + engineer + developer	Usually one skill	Full mix in one team
Continuity	Turnover risk	Leaves when project ends	Replacement process, documentation
Ramp-up	Months	Fast	Typically 1–2 weeks
Governance	Depends on team	Rarely documented	KPI dictionary, lineage, SLA

Which dashboards usually come first?

Management overview: revenue, margin, cash and key operational KPIs
Sales performance: pipeline, targets, conversion and customer segments
Finance: budget vs actual, P and L by unit, receivables ageing
Operations: stock, service levels, delivery performance

Risks and mitigations

Conflicting numbers: KPI dictionary with business owners signed off before build.
Poor source data: data quality tests and exception reports, fixes at source.
Low adoption: involve users early, training, usage tracking.
Vendor lock-in: code in your repositories, full documentation, assets in your tenant.
Security gaps: row-level security, least-privilege access, audit logs.

Security, data protection, NDA and IP

We work in your cloud tenant or infrastructure with named accounts and MFA. Data stays in your environment; personal data is minimised or pseudonymised where possible. Pipelines, models, dashboards and documentation are your property.

A note on the contract model

We work under a B2B service agreement with a statement of work, SLA annex and change procedure. Intellectual property in deliverables (rules, reports, code, designs, documentation) is assigned to you on payment, and a mutual NDA is signed before any data is shared. Where we process personal data on your behalf, we sign a GDPR-compliant data processing agreement (DPA) with Standard Contractual Clauses, or the UK IDTA/Addendum for UK clients, and we operate under Turkey’s KVKK. Team members are employed by 360 Soft under Turkish labour law; we remain responsible for their management and replacement. This is general information, not legal advice; please have your counsel review the final contract.

Vendor selection checklist

Does the vendor start with KPI definitions, not just visuals?
Are pipelines and models stored in your repositories and tenant?
Is there a data quality testing approach?
Are SLAs defined for refreshes, incidents and change requests?
Is a GDPR DPA with SCCs and KVKK compliance in place?
Can the team cover both engineering and analysis?
How are knowledge transfer and staff replacement handled?

Frequently asked questions

Which BI tool should we choose?

It depends on your existing licences, data platform and skills. Microsoft-centric companies often choose Power BI, while Tableau and Looker suit other stacks. We compare options neutrally.

Do we need a data warehouse?

For more than a few sources or for historical analysis, yes. Small set-ups can start with direct connections and move to a warehouse later.

Can you work with our ERP?

Yes. We regularly integrate ERP, CRM, e-commerce and finance systems via connectors, databases or APIs.

How long until the first dashboard?

A first priority dashboard is typically live within 4–8 weeks, depending on data availability.

Who owns the dashboards and code?

You do. All assets are built in your tenant and repositories and are assigned to you.

Can you also do ad-hoc analysis?

Yes. Analysts handle one-off questions and deep dives alongside routine reporting.

How is data security handled?

Through work in your environment, named accounts, MFA, row-level security and a GDPR DPA with SCCs.

Can you take over existing reports?

Yes. We inventory, document and rationalise existing reports before improving them.

Do you provide user training?

Yes, for both report consumers and power users who build their own views.

How quickly can a team start?

Typically within 1–2 weeks after the scope is agreed.

Let us clarify your reporting needs together

Tell us about your data analytics and BI needs and we will come back with a scoped proposal, a team plan and a realistic start date (typically 1–2 weeks). Call +90 850 335 10 87, message us on WhatsApp, email info@360-soft.com or use the contact page. 360 Soft Marketing Yazılım ve Danışmanlık Ltd. Şti., Nidakule Ataşehir Batı, Barbaros Mah. Begonya Sk. No:1 D:2, 34746 Ataşehir/İstanbul.

Related services

All services: Outsourcing Services