Data Integration
Connect suitable information from multiple systems into a structured reporting environment.
DATA INTEGRATION & PREPARATION
Connect Your Data. Prepare It For Insight.
Bring suitable business data together from spreadsheets, databases, Microsoft platforms, business applications and APIs — then clean, transform and structure it for Power BI, reporting and analytics.
Discuss Your Data
01
Connect Sources
Bring suitable business data sources together.
02
Clean Data
Prepare inconsistent records for structured reporting.
03
Transform Data
Reshape information around reporting requirements.
04
Reporting Ready
Create a stronger foundation for analytics and dashboards.
01
Overview
BEFORE THE DASHBOARD COMES THE DATA
Better reporting starts with better-prepared data.
Business information often exists across Excel files, SQL databases, SharePoint, Dataverse, ERP systems, CRM platforms, operational applications and other data sources.
Before that information can support useful reporting, it may need to be connected, cleaned, standardized, combined and transformed into a structure suitable for analysis.
Incodiv Tech helps organizations prepare suitable business data for Power BI, management reporting and analytics by building practical data integration and transformation workflows around the available technical environment.
02
Capabilities
DATA FOUNDATION CAPABILITIES
From disconnected information to structured reporting data.
Data Cleaning
Address inconsistent values, formatting issues and other reporting preparation needs.
Data Transformation
Reshape and transform source information into structures suitable for analysis.
Dataset Combination
Merge or append compatible datasets where business and technical requirements allow.
Data Mapping
Align fields, identifiers and business definitions across different data sources.
Power Query
Build transformation steps for suitable Power BI and Microsoft reporting scenarios.
SQL Data Preparation
Use SQL queries and reporting datasets to organize suitable database information.
API Data Integration
Work with available APIs where supported to bring external application data into reporting.
Data Quality Review
Identify reporting issues such as missing, inconsistent or duplicated information.
Reporting Tables
Structure suitable datasets around reporting dimensions, measures and business needs.
Refresh Planning
Plan appropriate refresh approaches based on source systems and Power BI setup.
Power BI Readiness
Prepare suitable information for data modeling, measures, KPIs and dashboards.
03
Business Challenges
WHEN DATA EXISTS BUT DOESN'T WORK TOGETHER
Different systems. Different formats. Different answers.
01
Data Lives Everywhere
Business information may be spread across spreadsheets, databases, applications and cloud platforms.
02
Inconsistent Formats
Dates, names, codes, categories and other values may be stored differently across source systems.
03
Repeated Manual Preparation
Teams may repeatedly copy, clean, merge and restructure data before producing reports.
04
Duplicate Records
Similar records may appear more than once or use different identifiers across multiple datasets.
05
Missing Business Definitions
Teams may use different interpretations for customers, revenue, status, categories or other reporting terms.
06
Dashboards Become Difficult to Trust
Reporting quality can suffer when underlying source data and transformation logic are not properly structured.
04
Data Pipeline
FROM SOURCE TO REPORTING
Build a clearer path from raw data to insight.
01
Connect
Access suitable source information.
02
Clean
Address data quality and consistency issues.
03
Transform
Reshape information for reporting.
04
Model
Organize relationships and business measures.
05
Analyze
Build reports, KPIs and dashboards.
05
Data Sources
CONNECT BUSINESS INFORMATION
Work with data across different business environments.
The appropriate integration method depends on the source system, available connectors, APIs, database access, authentication, permissions and reporting requirements.
Excel
CSV & Flat Files
SQL Server
MySQL
SharePoint
Dataverse
ERP Systems
CRM Systems
REST APIs
Business Applications
Sales & POS Data
Operational Systems
06
Data Cleaning
IMPROVE REPORTING CONSISTENCY
Clean the information before measuring it.
Data preparation can address common structural and consistency issues before information is used in dashboards and management reporting.
01
Missing Values
Identify fields where important reporting information is unavailable.
02
Duplicate Records
Review potential duplicates using appropriate business identifiers.
03
Formatting
Standardize suitable dates, text, numbers and other field formats.
04
Naming Consistency
Align suitable categories, statuses and naming conventions.
05
Invalid Values
Identify values that do not align with expected reporting rules.
06
Data Types
Structure columns using appropriate types for reporting calculations.
07
Transformation
RESHAPE DATA AROUND BUSINESS NEEDS
Convert raw structures into reporting structures.
Source systems are usually designed to support operational processes. Reporting may require that information to be reshaped differently.
Select & Rename
Keep relevant fields and use reporting-friendly naming.
Merge
Combine related datasets using suitable common identifiers.
Append
Combine compatible rows from multiple similar datasets.
Filter
Include records relevant to the reporting requirement.
Derived Fields
Create suitable calculated or categorized reporting fields.
Group & Structure
Organize information around reporting dimensions and levels.
08
Power Query
REPEATABLE DATA PREPARATION
Structure transformation steps for Power BI reporting.
For suitable Microsoft reporting scenarios, Power Query can be used to connect, filter, reshape, combine and prepare information before it reaches the reporting model.
01
Connect
Source data
02
Transform
Preparation steps
03
Combine
Related information
04
Load
Reporting model
09
SQL Preparation
DATABASE REPORTING FOUNDATION
Prepare database information for clearer reporting.
Where suitable database access is available, SQL can help organize operational information into datasets designed around reporting and analytics requirements.
01
Queries
Retrieve relevant information for reporting requirements.
02
Joins
Connect related tables using appropriate database relationships.
03
Reporting Views
Structure reusable reporting layers where appropriate.
04
Aggregation
Prepare summarized information for suitable reporting scenarios.
10
Data Mapping
ALIGN DIFFERENT SYSTEMS
Make different data sources speak the same language.
Combining systems often requires more than matching column names. Customer identifiers, product codes, branch codes, statuses and other business keys may differ between systems.
SYSTEM A
CustomerID
ProductCode
BranchID
Status
MAP
REPORTING MODEL
Customer Key
Product Key
Location Key
Reporting Status
11
Data Quality
REPORTING QUALITY DEPENDS ON SOURCE QUALITY
Find data issues before they become dashboard issues.
Transformation can improve the structure of information, but it cannot automatically make incomplete or incorrect source records accurate. Source quality and business definitions remain important parts of reliable reporting.
01
Completeness
Are important reporting fields populated?
02
Consistency
Are values represented consistently across sources?
03
Uniqueness
Are business records uniquely identifiable?
04
Validity
Do values follow expected business rules and formats?
12
Reporting Model
PREPARE FOR ANALYTICS
Organize data around business questions.
Once source information has been prepared, the reporting structure can be designed around relevant dimensions, transactions, relationships, measures and reporting requirements.
DIMENSIONS
Customers
Products
Dates
Locations
REPORTING
DATA MODEL
Relationships + Measures
BUSINESS ACTIVITY
Sales
Purchases
Inventory
Finance
13
Power BI Readiness
BUILD ON A STRONGER DATA FOUNDATION
Prepare data before designing the visuals.
A dashboard is the visible part of a reporting solution. Behind it are source connections, transformation steps, relationships, calculations, business definitions and refresh considerations.
01
Connections
Suitable data sources can be accessed.
02
Transformations
Preparation logic is structured.
03
Relationships
Reporting entities are connected.
04
Measures
Business calculations are defined.
05
Reporting
Data supports intended analytical views.
14
Refresh & Connectivity
KEEP REPORTING CONNECTED
Plan how data reaches the reporting environment.
Data refresh and connectivity should be planned according to the source platform, network, gateway requirements, connector capabilities, permissions and Power BI environment.
Source
Database, file or application
Connection
Connector, API or gateway
Refresh
Appropriate refresh approach
Reporting
Power BI and analytics
Refresh frequency and available connectivity depend on the selected data source, Power BI architecture, gateway configuration, licensing and technical environment.
15
Architecture
CONNECT THE REPORTING LAYERS
A practical architecture from systems to decisions.
LAYER 01
Business Systems
ERP • CRM • Excel • SQL • Apps
LAYER 02
Integration
Connectors • APIs • Queries
LAYER 03
Preparation
Clean • Transform • Map • Combine
LAYER 04
Reporting Model
Relationships • Measures • KPIs
LAYER 05
Business Intelligence
Dashboards • Reports • Analysis
16
Use Cases
CONNECT DATA ACROSS BUSINESS AREAS
Prepare information for different reporting needs.
01
Sales Reporting
Combine customers, orders, products and sales activity.
02
Financial Reporting
Prepare suitable financial information for analysis.
03
Inventory Reporting
Structure products, warehouses and stock movement data.
04
HR Reporting
Prepare workforce, attendance and department information.
05
Operations Reporting
Connect operational activity and process information.
06
Executive Reporting
Bring selected KPIs from multiple business areas together.
17
Technology
DATA & ANALYTICS TECHNOLOGY
Technologies for connected reporting environments.
Power BI
Power Query
DAX
SQL Server
T-SQL
MySQL
Excel
CSV
SharePoint
Dataverse
REST APIs
Power Platform
Microsoft 365
Business Applications
18
Our Process
FROM DISCONNECTED DATA TO REPORTING FOUNDATION
Structure integration around actual reporting requirements.
01
Discover
Understand reporting goals, users and business questions.
02
Assess
Review available systems, files and source data.
03
Map
Identify fields, relationships and business definitions.
04
Prepare
Clean, transform and combine suitable information.
05
Validate
Review prepared data against agreed reporting requirements.
06
Connect
Prepare the reporting layer for analytics and dashboards.
19
Why Incodiv
DATA + BUSINESS SYSTEMS + REPORTING
Integration designed with the reporting goal in mind.
Incodiv Tech works across Power BI, Power Query, SQL databases, Microsoft technologies, APIs and custom business applications.
This helps us approach data preparation from both sides — understanding where the information comes from and how it needs to support reporting.
01
Power BI & analytics experience
02
SQL & database experience
03
Power Query transformation
04
Microsoft ecosystem integration
05
Custom application integration
06
Business-focused reporting structure
20
Related Services
CONTINUE YOUR DATA JOURNEY
Turn prepared data into business intelligence.
21
FAQ
COMMON QUESTIONS
Data integration and preparation, explained.
What is data integration? +
Data integration is the process of bringing suitable information from different systems, databases, files or applications together for a defined business purpose such as reporting or analytics.
Why is data preparation important for Power BI? +
Power BI reporting depends on the structure and quality of the underlying information. Data preparation helps clean, transform and organize source data before it is used in reporting models and dashboards.
Can you combine Excel, SQL and other data sources? +
Yes, where the sources are technically accessible and suitable relationships or business mappings can be established. The appropriate approach depends on the systems and reporting requirements.
Can you clean our existing Excel data? +
Yes. Existing spreadsheet structures can be reviewed for issues such as inconsistent formats, missing values, duplicate records and reporting preparation requirements.
Do you work with APIs? +
Yes. API-based integration can be considered where a suitable API is available and the required authentication, permissions and technical access can be provided.
Can you prepare SQL data for Power BI? +
Yes. Depending on the database and access available, SQL queries, joins, reporting views and other suitable structures can support Power BI reporting requirements.
Can data refresh automatically? +
Supported refresh approaches depend on the data source, connectivity method, gateway, Power BI environment, licensing and other technical considerations.
Can you improve an existing Power BI data model? +
Yes. Existing source connections, Power Query transformations, relationships, measures and reporting structures can be reviewed to identify practical improvements.
YOUR DATA SHOULDN'T STAY DISCONNECTED
Build a stronger foundation for reporting and analytics.
Tell us where your business data currently lives, how your team prepares reports today and what you want Power BI or management reporting to show.
Discuss Your Data Integration