Data Integration Services for Implementing Advanced Analytics Using Power BI
What are different data sources and their types:
The term ‘Data Source’ simply means what the name suggests. It is the source from where the organizations acquire important data. Later, this data forms the basis of data integration services. The purpose of these heterogeneous data sources is to assist users or applications to access the data and transport it to the database of the instant user.
Here, certain tools are used by the company to perform database integration services. These data sources can be classified into the following:
- External Data Sources – An external data source is defined as the connection between the user database with an external database. External data integration services are performed with the data acquired from these sources.
- Internal Data Sources – Internal data sources are the original site of the data that arises within the business procedures of an organization. Companies have absolute access to this form of data. Internal data integration processes are performed with this data.
What is the data integration process and its benefits for an organization:
‘Data Integration’ is the process of bringing together the data derived from a variety of sources in an integrated view. This data is then made accessible to the users connected to the specific network after performing advanced data integration. Organizations can gain a real-time view of their business through enterprise data integration methods.
This process provides several advantages to the user organization which are as follows:
- Database integration services provide real-time access to the business information which increases the decision-making in the organization.
- Real-time access to customer information improves the customer experience for the company.
- Integration technologies positively impact the performance of the various departments of a company.
- Lastly, application integration of data helps in applying the acquired relevant information in increasing a company’s production capacity.
What are some key terms in the data integration process:
The following key concepts need to be understood concerning data integration services:
- Data Import – Data Import is the system used to integrate the data gathered from external sources with the data collected from analytics. This integrated form of data can then be used for the organization and analysis to reflect the relevant information of an organization’s business. This is one of the several data integration platforms that companies use for business purposes.
- Data Export – The process of formatting a set of data in a way that enables another application to use the same data set is termed data export. An application is said to export data when it can create a file of the acquired data in a format that makes it easier for another application to use the same data.
- Data Replication – Data Replication consists of a method of the constant transaction of data collected from a variety of sources. This procedure ensures that the data set in the database of the user organization reflects or is the same as the source of the dataset. The method of data replication aids in enterprise data integration processes.
- Data Mapping – The basic procedure to be followed before beginning the various data integration services & activities like data migration, integration, and others. This data mapping task is the process of matching the various fields of two or more databases. The method is used to remove the existing differences existing between the two systems.
What are the challenges faced during the data integration process:
The integration capabilities of an organization are judged based on the integration of it’s external and internal data sources. But, there are several challenges in the completion of this process which are as follows:-
- Different formats – Both the internal and external sources of data usually contain information in different formats which makes it difficult to perform data integration successfully.
- Lack of easily available data – Sometimes, an organization may have a poorly performing data integration platform. This can be caused due to the lack of easy access to data by all the teams in an organization.
- Old data sets – In a situation where the datasets being integrated from internal and external data sources are outdated, the integration processes may suffer.
- Incorrect Software – Finally, if a company uses incorrect software while attempting to integrate internal and external data sources, the process might pose a huge challenge.
Working with data sources in Microsoft Power BI
In Power BI, the term data source refers to the final path from which the relevant organizational data is accessed. Moreover, some examples of data sources include the path to a file in the hard disk, a URL to a Facebook account, or the location of a database on a cloud computing system.
All of these can be considered substantial data sources. As per data integration services experts, these data sources can be accessed with the help of Microsoft BI applications and tools. A user organization can access several data sources through the Power BI Desktop. This data connectivity can be achieved from the Home ribbon. The most common kinds of data are visible on the Get Data menu.
This Get Data dialogue box arranges the kinds of data in the following categories:
- Power Platform
- Online Services and
What are supported data sources in Power BI:
The Power BI platform is known for its capacity for supporting a wide variety of data sources. The Get Data option can be clicked by a user to view the available options of data connections. This platform allows an organization’s system to connect to various files, for instance, flat files, Azure Data Factory, or other databases.
It can also provide access to several web platforms like Facebook, Google Analytics and others. The system also uses an ODBC connection to connect to other ODBC sources of data.
Some of the data sources supported by the Power BI platform are as follows:-
- Flat Files
- SQL Database
- OData Feed
- Blank Query
- Azure Cloud Platform
- Online Services
- Blank Query
- And some other data sources like Hadoop, Exchange and Active Directory.
The Power BI Desktop is designed to depict the available data sources to the user organization in the Get Data option. After clicking this option, the generally available data options are displayed. The user can choose from the visible options or otherwise click on More to see the additional data sources which can be supported by the Microsoft BI platform. Because of various data sources available in Power BI, many data integration services give first priority to MS Power BI.
What is Power BI Data Connectors: A brief Overview
A Data Connector is a pathway of transporting a dataset from one database to another. Commonly, these processes also include the procedure for filtering and transforming datasets into a certain coherent format or structure. This is done for proper analysis or query solving.
In Microsoft BI, data connectors are used to access and connect to data from any application, service, database or data source. The platform also allows the process of developing customized data connectors in order to facilitate the data analysis process in the Power BI Desktop.
The custom data connectors of the Power BI platform enable cloud integration of data by permitting the process of refreshing the data through the on-premises data gateway. The reports published in the Power BI sources can then be refreshed in the same process. In the revised version of the on-premises data gateway, the Load Custom Data Connectors option is available.
This can be accessed by the user using the Gateway service. Once the option for using the custom data connector is selected by the user, the available connectors can then be used for refreshing reports in the Power BI Service.
EPCGroup provides data integration services in Microsoft Power BI for implementing business intelligence solutions. We have over 75+ In Power BI consultant experts with over 100+ years of combined experience.
What is Hybrid Data Integration in Microsoft Power BI:
In the contemporary world, organizations use several sources in order to acquire meaningful data relevant to their business pattern. Later, these sets of data are analyzed using visualizing tools such as Power BI. But, I. Order to perform proper data analysis, the stored data needs to be converted into a format that is similar to the internal data format of the organization.
In order to aid in this process, the Power BI platform provides a wide range of technologies and tools in order to perform the process of preparing the data sets and later integrating them with the enterprise data. But, an organization is responsible to choose the suitable tool for this purpose for themselves.
The choice will depend on the roadmap of the Microsoft’s product, the needs of the organisation, security, data refreshing frequency and other requirements.
Some of the hybrid data integration tools of Power BI are as follows-
- Microsoft SQL Server Integration Services
- Azure Data Factory
- Data Flows
- Azure Stream Analytics
- Power Query
Data Integration Services: An EPC Group Approach
In the current business world, the EPC Group is leading large-scale organizations to success through its state-of-the-art IT services and data integration techniques. The group is scoring in the competitive market in providing data integration solutions to companies due to certain positive impacts they have been able to show.
Some of them are as follows:
- The service is built on a Microsoft SQL engine which is why it provides data integration at lighting fast speed.
- Secondly, the computing procedure meets the demand of the user organization and at the speed required by the company.
- Lastly, the final end product is seamlessly integrated data stored into the database of the organization.
In conclusion, it can be said that the Power BI provides for works class data integration services in a cost-effective pattern. The user organizations can benefit from the use of these services in the long run.