Interactive, ready to use Power BI reports and dashboards
Applicable for virtually every data source - one model and one source of truth
Can be based on your current systems (ERP/CRM/TMS/WMS and others)
Automatic refresh, further development and maintenance possible with internal resources
In short about Power BI Deployment
Power BI implementation allows increasing the work efficiency by a huge margin (reporting automation unleashes the potential of
specialists and managers in your organization)
Scattered, diversified, and disintegrated Data Sources? ETL Data Integration through Advanced M, DAX, R, and Python
You can take the right action, find the problem root cause and identify the cost-saving opportunities with clear KPI's, measures, and optimization analysis
Applicable for virtually every data source - data from ERP (SAP, Oracle), CRM, SSAS & much more - tailored tools and highly or completely automated reports and visual management take your analytics to the next level
Not ready for a full-scale 3rd party implementation? Start the Power BI journey with one of our world-class workshops, organized both on-site and as a virtual classroom
There are various Power BI implementation strategies and we will help you to choose the right one. Want to learn more on your own? We prepared a clear guide on Power BI implementation scenarios
Want to start small but fast? Hire our consultants and developers with the entry package of 150 manhours. You will be amazed by what can be achieved with just that!
Interested? Contact us firstname.lastname@example.org
Power BI Implementation - more information
Power BI is a collection of desktop and cloud services, that lets the organization create breakthrough analytical tools,
reports, and dashboards and share them across the company in a more stable, safe, and faster way than ever before.
Implementing Power BI related solutions is one of Antdata's main business pillars.
Implementation of Business Intelligence solutions (and Power BI in particular) unequivocally increases the organization's capacity
and capability to understand its data and make right, data-based decisions.
In a truly revolutionary way, it helps to use in full not only the data but also the potential of the team members.
They have effectively more time to think about what the data means and take appropriate actions, instead of focusing on repeated, mundane, and never-ending
attempt to finish the calculation, making the right chart or slide. What is more, the data is displayed on state-of-the-art,
visually appealing and error-free dashboards.
The typical way of getting to the truth, to the right conclusions and ultimately taking action looks somewhat like this:
The data is gathered and stored in ERP/CRM/WMS/TMS/HR system(s). Sometimes one system embraces the majority of the firm's day-to-day operations,
sometimes multiple systems play a crucial role. Sometimes data is gathered in one master data repository, but that is a truly unique situation.
Usually, both systems and underlying data sources are scattered. We are talking here about company key data: finance, sales, manufacturing,
personal, and much more.
The sheer amount - width and depth of data is unique for every company. To manage it, the aforementioned systems often offer BI-like built-in functionalities.
Unfortunately, they tend to be very simple, they become outdated very quickly, its redesign is impossible or very expensive.
Not to mention the fact, that it can be done only with the hands of the system supplier’s programmers. So the only reasonable way means
using the built-in feature of exporting the system data to an Excel sheet, or, when it is impossible due to the platform limitations,
the IT department extracts the data directly from the system database on users’ requests.
However, the important part here is that databases, despite that there are myriad types and kinds of them – are standardized,
structurally similar to each other, and used by the systems as one of its components. Access to the database, irrespectively of
its type (whether it is MsSQL, MySQL, Oracle, and others) can be granted independently from the system.
It happens very often that to draw the right conclusions, we need to use multiple sources. How can we learn what the profit per 1 employee is if finance data
is stored in one system and HR data in the other? How can we calculate the pallet floor space moving cost if the formula ingredients come from both
the inside of the company and the systems of our logistics providers? As of now, the most common solution is using a spreadsheet and executing an attempt to
integrate the data. Unfortunately, process automation is limited or often impossible. Left with a huge amount of manual labor, the spreadsheets are prone to
errors, exceptions, and irregularities. Not to mention the fact, that created analysis and reports are static and allow an outlook from one angle at a time.
Changing the perspective requires multiplying the number of charts, tables. If we do not do that, we are confronted with very generic data. If we do that,
the number of elements to navigate through makes the report downright useless. Any problem from the list above alone disqualifies the analytical tool,
but they tend to appear simultaneously!
The solution to that is Business Intelligence class solution implementation. In our case, we recommend strongly Microsoft Power BI.
The implementation may take place as a standalone project or together with other Data Architecture components down the stream.
The examples include the creation of Azure Data Repository.
When you implement Power BI, you continue to use your current ERP/CRM/HR systems!
The important aspect of Power BI implementation is the fact it is complementary to currently used systems. There is no need for a revolution or big bucks purchase.
There is no operational threats, no conflicts with well-established procedures and processes. It allows us to make a leap forward in terms of efficiency and it does
it in a sustainable and very cost-efficient way.
Instead of creating repeated data dumps, tons of spreadsheet transformations and calculations, attempts to integrate
the data without automating and visualizing (or rather – trying to visualize it) using very basic charts,
you can replace that all with a Power BI data model and report.
Where to start?
It always starts with a call. You neither have to have a specific idea in mind, nor you need to be an expert in the field.
We will schedule a meeting and try to understand your needs and current data landscape. We will quickly try to define the potential scope of the implementation,
identify the data sources, and conduct a feasibility study. And yes, we will need to see your data and that is OK. Very strict NDA will make you comfortable and data security is our top priority.
Each implementation project is as unique as your business.
However, each successful implementation is based on four pillars:
Data preparation, including access and security
Data processing, including data model creation
Report deployment (RLS sharing included)
BI Architecture sample
The creation of the BI-class data architecture serves as a bridge connecting and integrating data from multiple sources.
The below example shows an automated solution based on integration with the ERP system and data coming from it. (SAP is just an example, it could be any other system of similar type)
Automated Power BI deployment
Efficient and productive implementation may be very well conducted for companies and/or departments that need to use flat files
(excel, .txt, or .csv files are perfect examples). This may take place for a variety of reasons, from security to data diversity or
the way the data is gathered.
Semi-automated Power BI deployment Implementation Project Duration
It depends on multiple variables and always is subject to thorough investigation and agreement with the customer. We however may assume, that the typical project lasts between 2 and 6 months.
Would you like to get more information?
To get to know more about Business Intelligence and Power BI click here.
You can also contact us by phone +48 518 748 589 or by e-mail email@example.com.