Jet Analytics vs. Microsoft Fabrics: Which One Fits Business Central Best?

Global Data 365
June 1, 2025

As organizations increasingly depend on data to drive smarter decisions, the tools used for data integration, reporting, and business intelligence are more important than ever. For users of Microsoft Dynamics 365 Business Central, two options often come into consideration: Jet Analytics and Microsoft Fabrics. But which one truly aligns with the needs of Business Central users—especially those looking for ease, speed, and clarity in reporting? Find the differences between Jet Analytics vs Microsoft Fabrics to find best fit for business central.

What is Jet Analytics?

Jet Analytics is a business intelligence solution built specifically for Microsoft Dynamics ERP systems, including Business Central and NAV. It combines pre-built OLAP cubes, a data warehouse, and visual ETL tools in an easy-to-use, Excel-integrated platform. At the core of Jet Analytics is the Jet Data Manager, which automates data extraction, transformation, and loading (ETL) without the need for heavy coding.

Jet Analytics is designed for rapid deployment, self-service reporting, and minimal IT dependency, making it ideal for finance, operations, and business teams that want quick access to accurate data.

What is Microsoft Fabrics?

Microsoft Fabrics is a new unified analytics platform from Microsoft that brings together data engineering, data integration, data warehousing, data science, and real-time analytics—all within the Power Platform and Azure ecosystem. It allows users to build end-to-end data solutions using tools like Data Factory, Synapse, Spark notebooks, Lakehouses, and Power BI.

While powerful, Microsoft Fabric is developer-oriented and designed to support large-scale, complex data environments. It requires strong technical skills and an in-depth understanding of multiple tools across Azure and Power Platform.

10 Key Differences for Business Central Users

Now, let’s compare how Jet Analytics and Microsoft Fabrics differ in real-world scenarios for Business Central users.

Feature	Jet Analytics	Microsoft Fabrics
Business Central Integration	Native, pre-built cubes and dimensions	Manual setup required
Tabular Cube Support	Out-of-the-box cubes for BC	Custom modeling via datasets
Data Warehouse Creation	Automated with Jet Data Manager	Manual via pipelines & lakehouses
Ease of Use	Built for business users, Excel-friendly	Developer-centric, steeper learning curve
Deployment Time	1–2 weeks	3–6 weeks or more
ETL Tool	Drag-and-drop visual ETL	Code-heavy tools (Data Factory, notebooks)
Licensing & Cost	Simple, fixed licensing	Usage-based, potentially unpredictable
On-Premise Capability	Available	Cloud-only
User Training & Support	Guided onboarding, strong partner ecosystem	Self-service or paid consulting required
Time-to-Insights	Fast, business-ready out of the box	Slower setup and modeling process

1. Seamless Integration with Business Central

Integration is one of the most important aspects when selecting a BI solution. Business Central users need tools that understand their data model, business rules, and dimensions—without requiring complex setup or custom mapping.

- Jet Analytics:

Jet Analytics provides deep, native integration with Business Central. It comes with pre-built cubes and ETL processes tailored specifically for BC data structures, enabling users to start generating reports quickly with minimal configuration.

- Microsoft Fabrics:

Fabrics requires manual configuration of pipelines or Power BI dataflows to connect with Business Central. This adds time, complexity, and potential for errors during integration.

2. Built-In Tabular Cube Support

Cubes provide structured, high-performance analytics for users needing fast, slice-and-dice reporting capabilities. The ease with which these cubes can be created and maintained is vital.

- Jet Analytics:

Jet Analytics includes built-in tabular cubes with drag-and-drop measures and KPIs. These cubes are pre-configured for business users and offer seamless integration with Excel and Power BI.

- Microsoft Fabrics:

Microsoft Fabrics supports tabular models through Power BI datasets, but requires custom modeling. Business Central users must build these datasets from scratch, increasing setup time and reliance on technical staff.

3. Automated Data Warehouse Creation

A robust BI solution must include a flexible and scalable data warehouse. Automating the creation and maintenance of this warehouse saves time and reduces the need for ongoing developer involvement.

- Jet Analytics:

Jet Analytics uses Jet Data Manager to automate data warehouse creation, manage historical data, and simplify maintenance. It eliminates the need for writing custom scripts or managing complex infrastructure.

- Microsoft Fabrics:

Microsoft Fabrics requires setting up data pipelines, lakehouses, and notebooks, which are typically suited for data engineers and not business analysts. The manual nature of these components increases implementation complexity.

4. Ease of Use for Business Users

An analytics platform is only valuable if the people who need insights can use it effectively. For many organizations, business users—not developers—are the primary consumers of data.

- Jet Analytics:

It is built for non-technical users, with a familiar Excel-integrated experience that reduces training time and increases adoption. Users can build and modify reports without relying on IT.

- Microsoft Fabrics:

Fabric is designed for technical professionals. It requires a solid understanding of Power Query, DAX, or Python, which limits its accessibility to business users.

5. Faster Deployment Time

Time-to-value is a critical factor when implementing analytics. The longer it takes to get up and running, the longer the organization waits for actionable insights.

- Jet Analytics:

With ready-made templates and native Business Central integration, Jet Analytics can be deployed in as little as 1–2 weeks.

- Microsoft Fabrics:

Because Fabric relies on custom development, pipeline configuration, and modeling from scratch, it usually takes 3–6 weeks or longer to get operational.

6. Visual ETL Tools

Transforming raw data into meaningful information should not require coding expertise. A visual ETL tool accelerates development and empowers non-developers to manage their data flows.

- Jet Analytics:

Jet Data Manager includes a visual drag-and-drop interface for ETL/ELT processes, allowing users to manage transformations, lookups, historical tracking, and data cleansing without writing code. This simplifies data preparation and empowers business analysts to control their own pipelines.

- Microsoft Fabrics:

Fabric requires the use of Azure Data Factory, Spark notebooks, or other developer-centric tools to build data pipelines. These tools offer flexibility but demand significant technical skills, making it unsuitable for business users or smaller teams lacking full-time data engineers.

7. Licensing & Cost

Understanding the licensing model is crucial for budgeting and long-term planning. Solutions that include everything under a single license often result in a lower total cost of ownership.

- Jet Analytics:

Jet Analytics provides a single license that covers Jet Data Manager, Jet Reports, and pre-built cubes, eliminating the need for multiple Azure services or unexpected usage-based costs. This makes budgeting and deployment more straightforward.

- Microsoft Fabrics:

Fabrics uses a capacity-based pricing model based on data storage, compute usage, and Azure services. This model can lead to unpredictable costs as data volumes or usage grow—especially for organizations with frequent report refreshes or large datasets.

8. Offline / On-Premise Capability

Not all businesses are ready to move fully to the cloud. Industries with data sovereignty concerns or specific IT policies may require hybrid or fully on-premise options.

- Jet Analytics:

Jet Analytics can be deployed on-premise, in a private cloud, or in the public cloud—giving organizations full control over their infrastructure based on compliance and security needs.

- Microsoft Fabrics:

Fabric is a cloud-native platform and does not support offline or on-prem deployments. This limits its suitability for businesses with strict data governance policies or disconnected environments.

9. User Training & Support

No matter how advanced a tool is, effective onboarding and support can make or break the success of an implementation—especially for non-technical users.

- Jet Analytics:

Jet Analytics offers partner-led training, user onboarding, and dedicated support to help organizations quickly realize value from their investment. The learning curve is short due to the Excel-based interface and pre-built assets.

- Microsoft Fabrics:

Fabric requires learning multiple components across Power BI, Azure Synapse, Data Factory, and more, making it challenging for new users. Support is generally limited to Microsoft documentation unless organizations invest in additional consulting or partner services.

10. Time-to-Insights & Business Value Delivery

Ultimately, the goal of any analytics solution is to deliver actionable insights quickly. The faster stakeholders get access to trustworthy data, the quicker they can make decisions that drive growth.

- Jet Analytics:

With pre-built cubes tailored for Business Central, intuitive visual tools, and Excel integration, Jet Analytics enables organizations to start analyzing within days—not weeks or months. Reports, dashboards, and KPIs are available out of the box, which accelerates ROI and ensures rapid business value.

- Microsoft Fabrics:

Fabric requires setting up multiple components (e.g., Data Factory, Lakehouse, Power BI datasets), coding data transformations, and building everything from scratch. This can result in weeks or even months before usable insights are available, especially for organizations without an in-house data team.

In Conclusion

While Microsoft Fabrics is a powerful analytics platform, it’s designed with data engineers and developers in mind. Business Central users looking for a solution that delivers fast time-to-value, ease of use, and built-in integration will find Jet Analytics to be the more practical, scalable, and cost-effective choice.

With its automated data warehouse, visual ETL, Excel-friendly experience, and faster deployment, Jet Analytics empowers business users to take control of their data—without the technical complexity of Microsoft Fabrics.

Simplify you Business Central Reporting with Jet Analytics!

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Top 5 Reasons Why Jet Reports is Built for Growing Businesses

Global Data 365
May 9, 2025

Growing businesses face unique and complex challenges, particularly when it comes to financial reporting. As companies expand, so does the volume of data they need to manage. Many rely on manual data handling, spreadsheets, or outdated reporting systems, which not only slow down processes but also increase the risk of errors. Inaccurate data or delays in reporting can prevent business leaders from making timely, strategic decisions. Effective and efficient reporting is the foundation of strong financial management and plays a vital role in the growth and sustainability of a business. Accurate, timely reports allow companies to analyze performance, manage cash flow, and forecast future opportunities or risks. However, traditional reporting tools and methods often fail to meet the needs of growing businesses. This is where Jet Reports stands out as a robust solution built specifically for Microsoft Dynamics ERP users. Growing businesses need more than numbers — they need real-time insights. That’s the power of Jet Reports for business.

How Jet Reports for Business Empowers Growing Companies?

In this blog, we will explore the top 5 reasons why Jet Reports is built for growing businesses and how it helps overcome common financial reporting challenges:

1. Faster Report Generation

In the fast-paced world of business, speed is critical particularly in financial reporting. Businesses need quick access to data that’s accurate and actionable to make informed decisions. The faster a report can be generated, the sooner a company can respond to market trends, internal challenges, or financial changes.

Jet Reports excels in enabling quick report generation by leveraging real-time connections to Microsoft Dynamics 365 and other ERP systems. This direct integration eliminates the need for manual data exports, data cleansing, and repetitive tasks. Reports that once took hours or even days to compile can now be generated in a matter of minutes, streamlining the decision-making process and giving businesses a competitive edge.

- Benefits:

Quick Report Compilation: Generate detailed reports within minutes rather than hours or days.
Real-time Decision Making: Immediate access to updated data allows for faster business responses.
Reduced Manual Errors: Automation minimizes human error caused by manual data handling.
Increased Productivity: Employees spend less time creating reports and more time analyzing insights.
On-Demand Reporting: Pull reports whenever needed without waiting for scheduled batch updates.
Comparison with Traditional Methods: Traditional reporting methods are time-consuming and prone to errors; Jet Reports automates these processes, drastically reducing the time needed to compile accurate reports.

- Example:

A retail chain previously spent 2-3 days compiling monthly sales reports manually. After implementing Jet Reports, they could produce complete, real-time sales reports within 30 minutes, allowing management to launch timely promotional campaigns and adjust inventory strategies dynamically.

2. Enhanced Security

As companies grow, data security becomes an increasingly important concern, especially when handling sensitive financial information. The risk associated with data breaches, unauthorized access, and data corruption can have devastating consequences, including financial losses and damage to a company’s reputation.

Jet Reports is built with robust security features, including data encryption and strict compliance with industry standards. This level of protection ensures that sensitive financial data remains secure, mitigating the risks of data breaches or unauthorized access. For businesses managing high volumes of financial information, these features are invaluable in maintaining compliance and safeguarding critical data.

Moreover, as financial data flows through various departments and systems, maintaining data integrity is essential. Jet Reports’ built-in security measures ensure that only authorized personnel have access to specific data sets, further enhancing security and reducing the chances of internal data leaks or misuse.

- Benefits:

Role-Based Access Control: Only authorized users can view or manipulate specific datasets.
Data Encryption: Jet Reports uses high-level encryption protocols to protect sensitive data from unauthorized access or breaches.
Compliance Standards: Adhering to SOC 2 and other relevant compliance regulations ensures that your business remains in good standing with industry standards.
Audit Trail Capabilities: Monitor who accessed what data and when, ensuring accountability.
Minimized Risk of Internal Leaks: Restricts sensitive reports to designated personnel only.

- Example:

A financial services firm needed to ensure that only senior accountants could access profit and loss statements. Using Jet Reports’ role-based access features, they easily restricted access by user roles, dramatically reducing the risk of unauthorized financial disclosures.

3. Real-time Data Accessibility

In an increasingly competitive business landscape, the ability to access real-time data is a game-changer. For growing businesses, having up-to-date financial information readily available enables more agile decision-making and more accurate performance assessments.

Jet Reports connects directly to ERP systems like Microsoft Dynamics, providing immediate access to the latest financial data. This eliminates the need for frequent manual data refreshes or reconciliations, which can lead to discrepancies or delays. Instead, business leaders can monitor KPIs such as revenue, expenses, and cash flow in real time, making it easier to spot potential issues before they escalate.

Having real-time insights is particularly crucial for industries that are dynamic and fast-changing. For instance, retail businesses with fluctuating inventory levels need to monitor stock movement, sales performance, and customer demand closely. With Jet Reports, they can immediately generate reports that reflect the latest data, allowing them to make proactive decisions about restocking, promotions, or pricing.

- Benefits:

Instant Insights: Real-time data enables quicker, more accurate decisions that can have an immediate impact on operations or financial performance.
Increased Accuracy: Reduces discrepancies caused by outdated data exports.
Proactive Issue Resolution: Identify and address risks before they escalate.
Better Resource Management: Quickly allocate budgets or staff based on the latest financial standing.
Impact on Business Operations: In scenarios like cash flow management or inventory tracking, having access to real-time data can be the difference between identifying a minor issue and facing a major financial problem.

- Example:

A wholesale distributor used real-time inventory reports generated through Jet Reports to manage their stock levels daily. This allowed them to optimize reordering processes and reduce overstock issues by 40%, improving cash flow management significantly.

4. Reduced Dependence on IT

One of the biggest advantages of Jet Reports for growing businesses is its ability to significantly reduce dependence on IT. In many organizations, finance teams rely heavily on IT departments to pull data from ERP systems, troubleshoot issues, or generate custom reports. This dependency not only slows down reporting but also puts a strain on IT resources.

Jet Reports, easy-to-use interface and direct integration with ERP systems empower finance professionals to manage reporting tasks independently. This allows businesses to operate more efficiently by freeing up IT teams to focus on higher-level projects and reducing bottlenecks in the reporting process.

- Benefits:

Self-Service Reporting: Finance users create reports themselves without waiting for IT assistance.
Faster Report Turnaround: Cut delays caused by IT backlogs and prioritizations.
Reduced IT Bottlenecks: By lowering dependence on IT for report generation, businesses can streamline their workflows and enable IT teams to focus on more strategic tasks.
Greater Agility: Finance teams can adjust and tweak reports on the fly as business needs evolve.
Cost Savings: Reduces overhead by minimizing the need for dedicated reporting IT staff.

- Example:

A mid-sized manufacturing company saved over 150 hours per quarter previously spent coordinating with IT for financial reporting. After adopting Jet Reports, their finance team could generate, customize, and analyze reports independently, allowing IT to redirect focus toward a major ERP upgrade project.

5. Ease of Use

One of key challenges for growing businesses is adopting new tools and systems without disrupting daily operations. Jet Reports is specifically designed to be user-friendly, making it accessible to non-technical users. Its intuitive interface ensures that finance teams can generate and customize reports without needing extensive training or relying on IT support.

This user-friendly design not only empowers finance teams but also reduces the strain on IT departments, which can focus on more strategic initiatives rather than being bogged down with report requests. Jet Reports comes with pre-built templates that users can easily customize, allowing for faster report generation and minimal time spent learning the system.

Additionally, the quick learning curve reduces the need for extensive training, making it easier for new hires or less-experienced team members to adapt quickly.

- Benefits:

Minimal Learning Curve: Most finance professionals can master it within a few sessions.
Pre-built Templates: Quickly generate essential 100+ financial reports samples without starting from scratch.
Drag-and-Drop Functionality: Simplifies report customization even for non-technical users.
Excel-Based Interface: Familiar environment reduces training needs.
Increased User Adoption Rates: Ensures company-wide buy-in and consistent usage.

- Example:

A growing tech startup with no dedicated reporting department needed quick reporting capabilities. Jet Reports’ Excel-based environment meant that their CFO and junior analysts were building complex financial reports within just a week of implementation, driving faster insights without hiring additional reporting staff.

In Conclusion

For growing businesses, having a powerful, scalable, and user-friendly financial reporting tool is critical. Jet Reports provides the speed, security, real-time insights, ease of use, seamless Power BI integration, and reduced IT dependence that businesses need to thrive. As companies scale, Jet Reports grows with them, ensuring that their reporting remains efficient and accurate.

If your business is looking for a reporting solution that can keep pace with your growth, contact us today to explore Jet Reports and see how it can help drive your success.

Grow your business with Jet Reports Today!

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Global Data 365 is composed of highly skilled professionals who specialize in streamlining the data and automate the reporting process through the utilization of various business intelligence tools.

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September 20, 2024

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Top 5 Reasons Why Jet Reports is Built for Growing Businesses Read More »

Data Lake vs Data Warehouse: What's The Key Difference?

Global Data 365
December 21, 2023

With the rise of big data and the explosion of new data sources, traditional data warehousing approaches may not be sufficient to meet the needs of modern data management and analytics, creating confusions between Data Lake vs Data warehouse. This has led to the development of new approaches, including Data Lake and Data Warehouse. Each approach offers unique benefits and drawbacks, and understanding the differences between them is critical to making informed decisions about data management and analytics.

Data Lake

A Data Lake is a centralized repository that allows businesses to store vast amounts of raw, unstructured, or structured data at scale. It provides a flexible storage environment, enabling organizations to ingest diverse data types without the need for upfront structuring. This unrefined data can then be processed and analyzed for valuable insights, making Data Lakes ideal for handling large volumes of real-time and varied data.

Benefits and Use Cases of Data Lake

Data lakes provide scalable and cost-effective storage, accommodating diverse data types such as raw and unstructured data for flexible analysis. With a focus on real-time analytics and advanced capabilities like machine learning, they support innovation in algorithm development. Cost-efficient storage solutions, often leveraging scalable cloud storage, make data lakes economical for managing large datasets.

Use cases range from big data analytics, IoT data management, and ad hoc analysis to long-term data archiving and achieving a 360-degree customer view. In essence, data lakes offer dynamic repositories that empower organizations with flexibility, real-time insights, and comprehensive data management solutions.

Data Warehouse

On the other hand, a Data Warehouse is a structured, organized database optimized for analysis and reporting. It is designed to store structured data from various sources in a format that is easily query able and supports business intelligence reporting. Data Warehouses are characterized by their schema-on-write approach, requiring data to be structured before entering the system, ensuring a high level of consistency for analytical purposes.

Benefits and Use Cases of Data Warehouse

Data warehouses offer a multitude of benefits, including optimized structured data analysis for improved query performance and efficient reporting. They preserve historical data for time-series analysis and audit trails, enhance business intelligence through data consolidation and dashboard creation, ensure data quality and consistency through cleansing processes, and provide scalability to handle growing data volumes.

Common use cases encompass business performance analysis, customer relationship management, supply chain optimization, financial reporting and compliance, and human resources analytics.

Find the visual representation and difference between: Data Lake vs Data Warehouse.

Data Lake vs Datawarehouse: Key Differences

Features	Data Lake	Data Warehouse
Purpose	Used for storing vast amounts of diverse data types for future analysis.	Optimized for large-scale analytical queries, storing historical data for reporting and analysis.
Data Type	Stores raw, unprocessed data in its native format.	Stores summarized, aggregated, and historical data.
Data Structure	Schema-on-read, allowing for flexibility in data storage.	Optimized for read-heavy operations (OLAP – Online Analytical Processing).
Users	Primarily used by data engineers, data scientists, and machine learning teams.	Mainly used by business analysts, data scientists, and decision-makers for insights and reporting.
Data Volume	Holds vast amounts of unstructured and structured data.	Handles large volumes of historical data from various sources.
Performance	Performance can vary; optimized for large data ingestion rather than query speed.	High performance for complex queries and large-scale data retrieval for analysis.
Schema Design	Uses a flexible schema design; data is often stored without a predefined schema.	Denormalized schema (e.g., star or snowflake schema) for faster query performance.
Data Processing	Processes a wide variety of data types, including structured, semi-structured, and unstructured data.	Processes complex queries requiring significant data aggregation.
Concurrency	Supports high concurrency for data ingestion and retrieval.	Supports a lower number of users.
Storage Cost	Typically cheaper to store vast amounts of data due to lower storage costs.	Higher storage costs due to large datasets and complex processing requirements.
Example Use Cases	Data exploration, machine learning, real-time analytics.	Business intelligence reporting, trend analysis, forecasting, decision support.
Data Source	Captures data from various sources, including social media, IoT devices, and unstructured data.	Aggregates data from multiple sources, including databases, external systems, and log files.

Data Type:
Data Lake: Stores raw, unprocessed data in its native format.
Data Warehouse: Stores summarized, aggregated, and historical data.
Purpose:
Data Lake: Used for storing vast amounts of diverse data types for future analysis.
Data Warehouse: Optimized for large-scale analytical queries and historical data analysis.
Data Structure:
Data Lake: Schema-on-read, allowing for flexibility in data storage.
Data Warehouse: Optimized for read-heavy operations (OLAP – Online Analytical Processing).
Users:
Data Lake: Primarily used by data engineers, data scientists, and machine learning teams.
Data Warehouse: Mainly used by business analysts, data scientists, and decision-makers for insights and reporting.
Data Volume:
Data Lake: Holds vast amounts of unstructured and structured data.
Data Warehouse: Handles large volumes of historical data from multiple sources.
Performance:
Data Lake: Performance can vary; optimized for large data ingestion rather than query speed.
Data Warehouse: High performance for complex queries and large-scale data retrieval.
Schema Design:
Data Lake: Uses a flexible schema design; data is often stored without a predefined schema.
Data Warehouse: Denormalized schema (e.g., star or snowflake schema) for faster query performance.
Data Processing:
Data Lake: Processes a wide variety of data types, including structured, semi-structured, and unstructured data.
Data Warehouse: Processes complex queries requiring significant data aggregation.
Concurrency:
Data Lake: Supports high concurrency for data ingestion and retrieval.
Data Warehouse: Supports a lower number of users.
Storage Cost:
Data Lake: Typically cheaper to store vast amounts of data due to lower storage costs.
Data Warehouse: Higher storage costs due to large datasets and complex processing.
Data Source:
Data Lake: Captures data from various sources, including social media, IoT devices, and unstructured data.
Data Warehouse: Aggregates data from multiple sources, including databases, external systems, and log files.
Example Use Cases:
Data Lake: Data exploration, machine learning, real-time analytics.
Data Warehouse: Business intelligence reporting, trend analysis, forecasting.

Finding the Right Fit: data lake vs data warehouse

Is there room for both Data Lake and Data Warehouse in your data strategy? Explore the benefits of adopting a hybrid approach, seamlessly integrating the strengths of both solutions for comprehensive data management. Discover the factors to consider when choosing between Data Lake and Data Warehouse solutions. From cost considerations to scalability needs and varying data types and formats, find the perfect fit with Global Data 365 for your business’s unique requirements by contacting us now.

Simplify Your Data – Get a Free Consultation!

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Power BI with Jet Analytics

Global Data 365
September 24, 2022

Business intelligence is a much better and less expensive choice than data warehousing for 90% of small to mid-size businesses. Both systems used together; Power BI with Jet Analytics have the same overall goal: to improve data analysis. The immense effort and cost needed to define the data tables and relationships required to drive analytics put data warehousing out of reach for most businesses. Due to the extreme minimal effort and expense needed to get it up and running, business intelligence is becoming the choice of small to mid-size companies, irrespective of which of the two most popular options are used.

Jet Analytics from insightsoftware (previously Jet Global) and Power BI from Microsoft are the two most popular business intelligence options in the Microsoft Dynamics environment. Jet Analytics can use either Excel or Jet Reports as a reporting tool, allowing you to have the best experience. Jet Analytics uses pre-defined data cubes to describe the patterns in the data necessary for reporting. Because the table relationships required for accounting, which are focused on financial processes, are not always the same as those required for business analysis, which could be more operational, this method works. This method has many disadvantages, including a higher initial cost, more work to create new data relationships into the data cubes, and the fact that data is only as current as of the last update.

A major benefit is the simplicity with which new reports can be created if they match the data cubes, as well as the improved accuracy since the reports are run against a replica of the output database rather than the live database itself. Data can be processed into data cubes from various sources, not all accounting systems.

Benefits of Using Power BI with Jet

Power BI depends on one or more databases to provide real-time or near-real-time data. This means that data is updated in real-time, but output for more detailed reports will not be optimal. Almost any form of the report can be created and distributed through the web or mobile devices. Every consumer can create their own dashboards, each with its own unique insight. It is possible to set up alerts. The details behind the reports can be drilled down by users. To use Power BI, you will need an Office 365 subscription.

You cannot really go wrong anyway. Invest a little more upfront to identify data relationships using data cubes in Jet Analytics or subscribe to Office 365 and use Microsoft BI Power to provide your users real-time access to important analytical data. To explore more about these better, less expensive alternatives for your company, we offer 30 days free trial license for you to test it on your very own database or get a personalized training for yourself.

Get a Free Demo of Power BI with Jet Analytics!

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Global Data 365 is composed of highly skilled professionals who specialize in streamlining the data and automate the reporting process through the utilization of various business intelligence tools.

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Jet Analytics Data Warehouse

Global Data 365
March 26, 2021

To remain competitive, a business needs to implement a jet Data Warehouse system that can keep with future requirements. Preparing to implement an ERP system can be a challenging task. Data storage technology’s future will be characterized by speed, convenience, and efficiency. Many of Microsoft’s legacy GP, NAV, and SL customers are likely to be considering a shift to the new platform now that the company’s latest ERP software version for small and midsize businesses has been released.

Microsoft Dynamics 365 (D365 BC) is the next version of the Microsoft Dynamics NAV code base. It is expanding it to a more cloud-friendly platform and incorporating it more deeply than before with the remainder of the Microsoft stack. The process of data transfer is never an easy task, no matter which ERP system you are moving from. Some particular problems related to data transfer are there. Surprisingly, many of them can be easily handled using a data warehouse.

Although data warehouses have been built for a different reason (i.e. to store data for big data analytics), they can provide tremendous value during an ERP transfer. That is because an entire data warehouse solution can pay itself from the savings generated by the process of migration itself. Enterprises have access to an increasing amount of data from all departments of their sector. Controlling how data travels through the enterprise becomes increasingly important as a company gathers data in different formats.

Data warehouse Obstacles during Data Transfer

Data warehouse technology has not changed much. However, the rise of Big Data and an excess demand for data has uncovered technical vulnerabilities that some legacy warehouses are not equipped to manage. One of the first questions asked from a project team when it comes to data transfer is which data is going to be moved from the old system to the new one? Firstly, all the data is going to be transferred. Secondly, many businesses have collected a large amount of historical data. Exporting data, filtering it, cleaning it, and reformatting it for the new system costs time and money.

Then the challenge arises of matching transactions. Bringing the list of the history of customer payments and invoices is a separate thing from recreating the history, providing the details of the payments made to certain invoices in certain amounts. On the other hand, the cloud model distinguishes storage from computing, resulting in a new level of cost and performance efficiency. Enabling IT to:

– Pay for only what is used.
– Gain total cost/performance leverage.
– Reduce duplication of data.
– Eliminating loading of data.
– Multiple platforms can access the same data.

If the company continues to retain the old system intact, it will cost them time and money. If only a single person knows how to operate the system leaves, or if the system update conflicts with the old ERP software. It will cost your company time on support and maintenance.

Jet analytics Data Warehouse as a Solution

Most ERP system manager fails to think of the alternative; a data warehouse solution that contains data from your old ERP system. It contains all of the data you require for historical reference. With a data warehouse, there is no need to handle transactions on the old system.

In comparison to the cost of maintenance of an old ERP system vs. a data warehouse, the data warehouse comes out on top every time. It not only solves the issue of historical ERP records but also serves an ongoing function as well. It significantly reduces security risks. The cloud has changed the way companies handle and store data for the better. To satisfy your existing and future business needs, cloud computing will help you create a new modern data infrastructure. Your organization now has the opportunity to harness its data’s potential, delivering unmatched productivity and ROI. You are finally ready to turn your data to reveal the deeper insights that will help you make better business decisions and produce higher-quality results.

Data Warehouse as a Migration Tool

By creating a standard data model for your old and new ERP systems within the data warehouse. You can utilize the data warehouse as a migration tool itself. You may proactively use the data harmonization process among the two platforms to clean and normalize data from the old system and prepare it for transfer to the new system.

Since most people think of a data warehouse primarily as a staging area for reports. This is a creative solution to the issue of data migration that is rarely suggested.

ERP Migration without Reformatting Reports

The future is hard to foresee, but one certain thing is that the most productive data warehouses are those that can use their data efficiently to optimize operations, anticipate market shifts, and boost availability. Similarly, Jet Analytics is a reporting platform from Global Data 365 that deals with the entire Microsoft Dynamics products, which include Microsoft Dynamics CRM, AX (Axapta), NAV (Navision), GP (Great Plains), SL (Solomon), BC, and Microsoft Dynamics 365 Finance and Supply Chain Management product.

The relation between Jet Analytics and the various products of Microsoft Dynamics operates independently. Users can extract data from the ERP system, which is integrated inside the data warehouse to a harmonized data structure. The customer records of both Microsoft Dynamics GP and Microsoft Dynamics 365 Business Central may appear the same in the data warehouse. Invoice records from various systems will also appear similar.

If you are thinking about transferring data from one system to another, particularly from Microsoft’s legacy ERP products to D365 BC, you can save time and money by implementing these approaches. Jet Analytics data warehouse can offer the following benefits:

– You can automate the removal and transfer of data that you intend to migrate by linking the Jet Analytics product to your old system, storing them in the data warehouse for import to the new system.

– You can tackle the issue of historical data by using Jet Analytics to provide unlimited access to data that is too difficult or costly to transfer. This decreases the probability of security breaches, saves recourses, and improves efficiency.

– If you have used Jet Analytics to develop reports for your previous Microsoft Dynamics ERP system. You can continue using the reports for data with little to no change from your new Microsoft Dynamics ERP system. This saves considerable time and money on implementation.

– You will have the most sturdy BI and reporting platform on the market after the migration, which will remove any potential reporting inefficacies.

A Detailed View over Time

The Jet Analytics data warehouse approach enables you to view both old and new data together as a single whole. Jet Analytics helps businesses to run comparative reports that look back through different years. Information is structure and interpreted by the data warehouse as if it originated from a single system.

Any level of compliance is involved in most ERP system implementations. One such compliance is the necessity of a complete break from the past. This particular problem is tackled effectively by the Jet Analytics data warehouse approach.

Jet Analytics Data warehouse as a Solution

For the success of any business, the present and future warehouse management systems need to embrace the incorporation of BI software solutions and visualization of insight. You can get started with Jet Analytics whether you have upgraded to the latest versions of Microsoft’s ERP system. There are many advantages to implementing a Jet Analytics data warehouse system.

– Jet Analytics can be deployed ahead of an ERP framework update to give you a head start, reduce risk, and lighten the overall implementation workload. When you finally introduce a new ERP system, report creation on Jet Analytics will continue to pay off.

– By acquainting yourself and your staff with the data warehouse setting, you can obtain an understanding of the benefits of implementing the Jet Analytics data warehouse system.

It is time to unlock the potential of your data to drive your business ahead. To learn more about how Jet Analytics can benefit your company or learn to improvise with Jet Analytics training.

Contact us to get more information.

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Global Data 365 is composed of highly skilled professionals who specialize in streamlining the data and automate the reporting process through the utilization of various business intelligence tools.

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Discover the power of Jet Analytics Cubes in revolutionizing your data analysis capabilities within Dynamics 365 Business Central (formerly NAV). Jet Analytics is a complete Business Intelligence solution that provides the answers to your mission critical questions. With little or no training users can quickly analyze issues from many different perspectives to discover trends in their business. Jet Analytics provides the strategic information users need to identify opportunities and proactively detect issues before they escalate.

When you implement Jet Analytics with Global Data 365, you get extra value for FREE. Global Data 365 offers you rich and advanced SSAS Cubes for Microsoft Dynamics 365 Business Central (NAV). Our cubes provide rich data analysis on following core modules:

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Payables
Purchase
Receivables
Sales
Service Management
Warehouse

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