Many of you will agree that businesses work better and attain more of their goals when they can utilize their data strategically. However, there are several forms and sources in which data exists in enterprises, such as CRMs, ERPs, mobile apps, etc. and combining and making use of that information is not as easy as it seems. Here, Data Integration Consultants come to your rescue and helps you make the most out of all your data.
For many years, companies were dependent on data warehouses with definite schemas for a specific use or application in the business. For example, marketing teams make use of data for better understanding the success of a specific campaign, get a clearer view of the buyer’s journey, or to plan the types and quantity of content they’ll require in the future.
As you all know, data is the most important asset, so suitably utilizing it can enable you to make intelligent business decisions, drive growth and boost profitability. However, as per Experian, 66% of companies fail to get a centralized approach to data, where data siloes have been one of the most common issues. With the growing amount of information available throughout the variety of sources, businesses are adopting a partial approach to data.
Luckily, automated data integration processes can collect structured, unstructured, or semi-structured data from virtually different sources into a single place. Combining data into a central repository facilitates teams across the enterprise to make performance measurement efficiently, get meaningful insights and actionable intelligence, and make more well-versed decisions to sustain organizational objectives.
What Is Data Integration?
According to IBM, data integration is a combination of technical and business processes used to connect data from different sources to extract meaningful and valuable information. In general, data integration creates a single, combined view of organizational data that is used by the business intelligence application to create actionable insights based on the completeness of the data assets, without concern about the original source or format. The huge amount of information generated by the data integration process is sometimes collected into a data warehouse.
A Combination of Theory and Practice
If it seems that this is something only for the enterprises that have huge data flows, you might be amazed to learn just how fascinating data integration is across different industries and sectors. In 2016, Capgemini surveyed that 65% of business executives said they fear to get inappropriate or uncompetitive if they fail to make use of big data. After the years of the survey, this percentage is continuously rising as executives across the world have realized the harmful impact of not including a data strategy and solution in place, which will affect every aspect of their business operations.
Today, staying competitive, work more capably, reducing costs and growing revenues means finding ways to collect, evaluate and optimize data to the fullest extent of its value. Data should not be treated as someday goals down the road, but as today’s driving initiative.
Data integration works throughout your organization to carry out numerous types of queries, from the coarsest questions to the overarching concepts. You can apply data integration to many detailed use cases that impact all teams and departments of your business, including:
Business intelligence – Business intelligence (BI) comprises everything from reporting to predictive analytics to operations, management, and finance. In addition, it depends on data existing in the whole organization to discover inefficiencies, gaps in processes, missed profitable prospects, and much more. Data integration provides you with the right BI tools and technologies that your company might need to make further strategic decisions.
Customer data analytics – Understanding who your customers are, what behaviors they show, and how they are expected to remain loyal or look somewhere else is vital to good business. Data integration allows you to extract information together from all your individual customer profiles into a unified view. From there, you can discover what the complete trends are and complement your existing customer retention strategies with real-time world insight.
Data enrichment – Fight against data decay by constantly updating contact lists like names, phone numbers, and emails. Merge this information with definite sets of exclusive information about every customer to create a much richer and more precise image of your buying audience.
Data quality – It is a challenge to manage the quality of data, it is important to ensure that your data requirements are reliable, that you understand how the data is generated and the tolerance for errors your organization is willing to accept. However, making the data integration process automatic eliminates many risks that are not conforming to your company’s data governance policies, growing both the accuracy and the value of the data available to teams across the organization.
Real-time data delivery – Businesses cannot wait days to provide actual numbers or insights; they have a few hours or sometimes minutes only. That’s why real-time data delivery is important for many businesses to adapt to customers, markets, vendors, and even general and compliance changes faster. Data integration allows you to check data from any point in the collection process anytime to find minute-by-minute insights into processes, workloads, and communications.
How Data Integration Consultants Plan Successful Projects?
Integrating various systems involves integrating different existing subsystems and then producing distinctive and new value for the customers or end-users. To make your efforts for integration planning successful, you must include a wide scope to make sure that the plan meets all specific business needs. A business analyst should start and direct every integration effort of systems to boost the success rate and reduce recurring tasks.
The process of integrating all data existing in different internal and external sources has become more complex in the last few years – typically because of a continuously growing massive volume of data handled by companies. And this process does not get any easier as new potential data sources continue to appear. The success of a data integration project does not only depend on the available systems, but also the third-party products you choose. Here are the most vital criteria to make your data integration successful...
Ensure that Data is of Good Quality
With the evaluation of Big Data, data quality has become a major concern in data-driven organizations. Any data integration task can be negotiated by bad quality data. Keeping it straight, if you keep the trash at one end, you will get nothing but trash at the other end also. Data integration projects without a company-broad strategy on data quality before, during, and after the data integration implementation process will certainly fail.
Good data quality is the only thing that will guarantee user-adoption and accordingly, the success of your data integration project. If you provide your users with poor quality data, they will begin to doubt the data existing in the system and will start using the old, idle processes. A successful data integration project should always have a dedicated data quality range.
Consider the Impact of System Customization
Even though, today, many systems and applications bring you an array of custom functionalities, many implementation projects contain additional customization and development practices to support enterprise-level, departmental or user-specific working processes and behavior. This process can result in numerous custom modules or capabilities, but it is also quite a challenge when it comes to integrating different systems.
Opt For a Consolidated Approach
When you adopt a data integration approach as a multitude of end-to-end custom integration scripts, without a general direction, then your data integration plan is considered to fail in delivering the required critical unified view of business data. Data must be coordinated in an automated and dependable manner across multiple platforms for a company to get a single version of the truth. Errors created by inconsistent data and manual data entry can prove to be very expensive for the organizations and interrupt business activities.
Take Future Upgrades into Considerations
Many ERP or CRM providers have developed an onetime integration between the systems for their consumers. Some organizations have already implemented this process for themselves. Although this might appear like a great idea initially as they have a good understanding of the complete processes and data models in the company, it can prove to be an error in the long term. Why? Because these integration solutions are not actually developed as a complete long-run project with future considerations.
So, what will the result be of upgrading the integrated systems? What will happen if you want to expand the use of your integration tools and integrate with other systems? When you select your data integration solution, always ensure that it is long-lasting, and you can keep using it when the integration collection changes. Personalized interfaces typically require development, which reduces the flexibility of the upgrades and makes maintenance more expensive.
Choose Top Management Support
Data management can be a challenging concern, some departments might consider that they own the data in their system and therefore be hesitant to allow other systems to access what they think to be their important information. Here is where wide executive support will help you. Although IT plays the most important part of your data integration project, it would be a big mistake if you do not involve more of your managers and executives.
Executive-level drives bring cooperation between data owners, user adoption, and are actually very important. Why? Because the data integration project you are implementing will not only affect your IT team but also have a broader impact on your overall organization. Don’t forget that a data integration project is all about sharing data and automating various processes. The best CRM-ERP integration projects cannot only be successful if they involve a CIO or IT director, but it also needs to include CEO-level support and participation of top management from the Sales and Marketing teams.
How is data integration implemented?
A diverse number of methods, manual and automated both, have been used for data integration earlier. A lot of data integration tools today utilize some form of the ETL (extract, transform and load) method. As the name suggests, ETL works by taking out the data from its host environment, converting it into some consistent format and then loading it into a target system to be used by applications operating on that system. The step of transformation generally includes a cleansing process that is executed to correct errors and insufficiencies in the data prior to its loading into the target system.
Various types of data integration tools are available out there, comprising master data management, data governance, data cleansing, data catalogs, data modeling and other tools that have a number of data integration features. Here are some of the generally used data solutions that businesses need to understand:
ETL Tools- As explained above, these tools extract data from one application or system, transform it into a fresh format, and then load it into the new application.
APIs– It refers to Application Programming Interface, which provides a programmatic approach to one application for sharing data with another.
Data Integration Platforms- It includes a broad range of diverse features, like ETL, ELT, data governance, data quality, data security, etc. These tools can incorporate data from an extensive variety of different sources and are appropriate for use by business users.
Integration Platform as a Service (iPaaS) – It offers cloud-based tools for the data integration process. They generally provide very effective ease of use features and the ability to integrate data from cloud-based sources, such as software as a service (SaaS).
Data Migration Services – They tend to migrate data from one place to another and may provide some limited features for data transformations as well. Most of the major cloud service providers present migration services for shifting data to the cloud.
Want more? There is so much more you need to know as a business user. As you have read, handling a data integration project is not as easy as it seems, so you will always require the guidance of data specialists who are experienced in handling such projects easily. ExistBI have experienced Data Integration Consultants based in the United States, United Kingdom and Europe. Contact us today to support your data integration project.