Are you seeking a better understanding of your business?
Have you missed opportunities due to insufficient or untrustworthy data?
Are you looking for new and better ways to achieve your business goals and boost the value your team is adding to the business?
Do you want to build a more solid foundation for decision making?
For many businesses, integrating data from various departments is the first step to achieving these goals--and many others. Data is now a pivotal component of any business strategy, but where do you start? You may have a long list of systems that don’t interact with one another but provide specific value to the departments using them. How do you connect that data without compromising its quality or the benefits the original systems provide?
You aren’t alone in asking these questions. Businesses across the globe are beginning their journey into using their data as an asset because they know it’s no longer an option, but a necessity. For most businesses, unused data is equivalent to money and opportunities left on the table. It’s time for your business to take a step forward in building a mature data strategy and capitalizing quickly on those opportunities.
In this guide, you’ll find core information about data integration that any business user should understand before planning a data integration project. You’ll also find essential information you should know when you’re evaluating potential service partners, as well as some quick bullets to share with leadership and other colleagues who haven’t yet discovered the value of data integration.
As always, if you have any questions about data integration, please contact us for a commitment-free consultation. Otherwise, read on to start building your data integration knowledge and find the perfect partner for your business!
Everything You Need to Know About Data Integration
What Is Data Integration?
Imagine how much more agile budget planning would be if the finance department had complete and always up-to-date visibility into data from all departments. Imagine if the sales and marketing departments got real-time updates on supply chain data like slowdowns in production and excess or low inventory. They could quickly capitalize on opportunities and help fill gaps in lockstep with what’s best for the business today.
These are just a couple simple examples of the immediate returns a mature data integration plan can offer. In reality, the benefits extend into every facet of the business for years to come. This is because data integration, a mature overall data strategy, and a modernized business intelligence plan aren’t just shiny new trends. They enable a more agile business that responds rapidly to evolving marketplaces to keep your business relevant, and they support decision making that actively drives your business toward its goals.
On top of creating a stream of data available across the organization, data integration also allows you to combine data from various sources to get a more complete picture, zooming in and out on various facets of the organization to see information in different ways. Combining a data integration strategy with data analytics and visualization tools is a step any business can take toward using their data as an asset. Keep reading to find out how to begin planning a data integration strategy.
How Does Data Integration Work?
The first step to successfully integrating your organization’s data--without creating a mess--is to step back to a big picture view and develop a comprehensive plan. Integrated data won’t be helpful to your colleagues unless you can offer them data they can trust.
First, you need to define what you want to achieve with your data. Don’t think in theoretical terms of what the data could do, or case studies you’ve read online. Think about your business and what it needs to achieve today and tomorrow. Think about times when the business has missed the mark. How could access to more comprehensive and accurate data help avoid similar situations?
Second, you need to gather an inventory of all possible sources outlining what types of data collected into which systems for each department. Look for colleagues in each department who understand the importance of developing a data integration strategy and will help you in your efforts. Building a network of data integration cheerleaders across the business will help you justify the investment needed to implement a successful plan and ensure its success by clearly defining needs across departments. In short, each department’s business needs are your data integration plan’s metrics for success.
Third, you will need systems to govern, update, and analyze your data. If you’re lucky enough to have a data scientist within your organization, they should be able to help you choose the best systems for your business. Otherwise, the prospect can be daunting. For a layman, it’s difficult to discern which system is best. Choosing the wrong systems can void the intended benefits of your data integration plan, and for some businesses can be a serious investment.
The most foolproof way to navigate this is to find a qualified data integration and data warehousing consulting service to assist. We know how important it is (and how difficult it can be) to find the right big data integration services partner. Every business needs a partner that understands not only the technical side of data integration but also the unique needs of your business and the complexities of the industry in which it operates. To help you in your search, we created this guide. By the end, you’ll know what to look for in a data integration center service.
For example, Onebridge is partnered with the most effective data analytics and visualization systems available, so we understand these systems and what they should offer inside and out. Looking for services that are well-versed and partnered with top analytics powerhouses like Microsoft and Tableau is a great first step to finding the right partner for you--but there are a lot more criteria to take into consideration. Now that you know everything you need to know about data integration, read on to find out what your data integration services partner should know.
Two Steps to Evaluating a Data Integration Services Partner
IBM defines data integration as “discovery, cleansing, monitoring, transforming and delivery of data from a variety of sources.” Data integration sounds pretty simple--you take all your data and put it together, right?--but there’s actually a lot more to those two words. Here are two things you should always ask any potential data integration services partner to find out if they’re really equipped to address all aspects of data integration.
1. Find out how they plan to prep for the implementation.
Here’s a simple checklist of steps any partner should include, at minimum, in the planning stages:
- Define goals. This should be approached from a highly analytical, business-first perspective. Data is a new facet to organizational effectiveness, so it’s easy to over-complicate by trying to define new data-specific goals. Focus instead on goals the business has already defined as a priority. Once they understand your data formats and sources, your partner should be able to help you connect the dots between the goals of the business and what the data can do.
- Define scope. Are there any instances you can imagine in the future where you might need to expand the scope of the data sources involved? Are there independent sales teams or partners that you’d like to eventually extend access to? Any potential partner should want to know this early in the process, demonstrating a concern for not only right-sizing the solution to your needs but making it work for you in the future rather than creating dependencies on outside organizations. The best partners place a focus on building internal data literacy to reduce outside dependencies. As the old saying goes, at Onebridge we think it’s important to teach our clients to fish for data insights rather than do all the fishing for them.
- Define data storage strategy. In short, this question could be defined as “in house server vs cloud vs hybrid.” Any potential partner should know the ins and outs of these options, easily articulating the pros and cons of each so you can discover which works best for you. This is definitely not a one-size-fits-all situation, so be wary of any partner that doesn’t offer options.
In fact, we want for you to be able to walk into any data integration meeting with as much prior knowledge as possible, so here are some basic pros and cons between server vs cloud vs hybrid storage:
In House Server
An in house server is kept onsite, so the first thing you need to consider is the upfront investment that you’ll have to make in hardware and maintenance support--not to mention the physical office space needed for the hardware. An in house server that is not backed up offsite is also vulnerable to physical damage like a fire or earthquake. There will likely be no guarantee regarding uptime--if the housing office loses connectivity, any onsite servers will also be unavailable to those outside that office, though those local will still be able to get access, which is an upside.
The most major concern in a strictly in house setup is the need for a comprehensive data security strategy, which is beyond the resources of many teams. On the flip side, with an in house server you have more physical control over your data storage, with no third party access. They can also be more cost effective for smaller organizations.
As you’d expect, many of the pros and cons of the cloud approach directly mirror those of in house servers. With the cloud, there’s no need for such a large upfront spend on hardware and IT resources, making it a particularly attractive option for companies that are growing quickly and are dependent on their data being constantly ‘up’ and available.
The cloud can also be cost effective long-term because users have options to pay for only the storage they use, upgrading and downgrading as needed. The cloud offers more regular and reliable backups to prevent data loss. Cloud services also typically offer built-in data security.
However, if the internet goes down on the cloud provider’s side, your data may be inaccessible. Cloud providers typically offer safeguards against this, but problems are always possible when data is placed offsite, so it’s a risk to consider. If data must be recovered, recovering from the cloud can be time-consuming.
The exact structure of a hybrid solution should be modeled on the needs of the business, but the core components obviously involve a mix of onsite and cloud storage. This can be an ideal strategy for a business to offset the downsides of a particular approach. Hybrid models offer flexibility and customization, which can also lead to significant cost savings. A good data integration services expert will be able to help you determine whether a hybrid approach is right and necessary for your business and design the perfect, forward-thinking solution for you.
For instance, you could use the cloud temporarily when resources are limited and external demand is high so your in house server doesn’t have to carry the load. An in house server can offer you high speeds when internal demand is high and external demand is low. From a cost perspective, hybrid approaches are usually highly scalable.
We’ve covered prepping for the implementation of a data integration strategy, now let’s take a look at the available integration approaches.
2. Find out which approach to data integration they recommend.
As the data science discipline has evolved, various approaches have been taken to data integration. Many businesses are still using the manual approach. The user locates the needed data themselves, imports it into a simple format like an Excel spreadsheet, and looks for comparisons and insights there. They may find a few interesting items, but they’re unlikely to discover anything groundbreaking or game-changing for the business. The process is too time-consuming and manual, and allows for only rudimentary understanding. This is obviously not a winning approach.
Another approach is to allow applications to do the work, computer programs built specifically to collect and manipulate data. The downside here is that those applications tend to be inflexible and highly specialized with always increasing complexity.
The most common approach today is data warehousing using the ETL (extract, transform and load) process to execute all kinds of tasks, like converting data formats to make data compatible. In other words, processes occur behind the scenes so you can get the easiest to interpret and most up to date view of your data possible.
There are a lot of different ways to design data warehouse architecture; just like hybrid data storage, the best design depends on the business. This is why it’s so important to find a data integration specialist who can help you design the ideal system that converts data without losing its integrity or quality.
Now that you know two of the most important signals that you’ve found a worthy data integration services partner, how do you go about justifying this need to the business? Below are some “reasons why” to share with leadership and anyone else you think could benefit from your data integration research efforts.
Justifying the Need: Benefits of Data Integration in Business
We’ve created a list below that you can easily copy and paste. Share this bird’s eye view with colleagues to give them a quick understanding of the benefits of data integration.
- Data flexibility and freedom. This is one of our favorite functions of data integration and a properly built data warehouse: the ability to convert data formats for compatibility without losing data integrity. This offers flexibility and freedom in combining and viewing data from different perspectives that your business has likely never experienced before. It also democratizes your data more than ever before, putting more eyes on it, giving it more transparency, and therefore allowing business users to move more in lockstep with one another as they are all referring to the same information. This allows teams a greater ability to use data to ideate innovative new solutions to old problems.
- Supported decision making. So many business professionals today make decisions based on their internal knowledge and gut feeling, usually because they don’t have trusted data available to them to base decisions on. We all know that the best business decisions are made when they are driven by facts and data, but getting from here to there can be very daunting. Data integration is a pivotal and manageable first step that offers all decision-makers a single source of truth.
- Maintain data quality. A mature data integration plan keeps data fresh and accurate, so users can rely on it. This builds data quality principles into the organization’s culture rather than making it a separate (intimidating) task requiring additional planning and resources.
- Data enrichment. When you combine different types and formats, you add another dimension to the information. That extra dimension can yield an entire spectrum of unexpected, hidden data insights.
- Cut through complexity. Especially in larger organizations, different departments are often collecting and managing data using different systems that address their specific needs. An effective data integration strategy allows you to cut through all those complicated interconnections to reduce the number of user interfaces and interactions needed to get to the data.
Data Driven Decision Making Matters Because Data Enables Intelligent and Agile Business Decisions
A data-driven organization understands that data is at the center of any business strategy. Companies must be able to use data not only to improve decision-making and operational efficiency, but they must have the capacity to create new products and processes based on data-driven insights. And as data-driven strategies take hold, analytics will become an increasingly important point of competitive differentiation.
That’s the new secret sauce: intelligent and agile business decisions. It isn’t complicated in theory--just in execution. That’s why it’s so important to find a data analytics service partner like Onebridge with both the technical and industry-specific expertise necessary to put you down the correct path to a mature, data driven business intelligence strategy.
If you agree that it’s time to stop making decisions based on poor quality data or the opinions of a few, and start making fact-based decisions supported by hard data, get in touch with Onebridge today. You can also join us in a conversation on Twitter, Facebook or LinkedIn.