Data professionals help business teams link strategy and execution because they have a superpower: they can make it easier for departmental business users — such as sales and marketing analysts — to find, understand and use customer data to make smarter decisions. With their support, departments throughout the organization are becoming increasingly data-driven.
But data professionals also have their kryptonite. Poor data access and processes can cause delays in go-to-market planning, erode data-led competitive advantage, and, at worst, steer the business in the wrong direction.
Disconnected systems and data silos cause suboptimal data management, which prevents business users from leveraging the power of customer data effectively or efficiently. However, if that data is connected and more easily harnessed to deliver business value, it gives the business a significant competitive advantage. The first step towards achieving that vision is getting data integration right.
Why Do Business Teams Need Data Integration?
Helping business teams get closer to the customers starts with connecting them to customer data. But, despite sophisticated technology stacks, customer data today remains siloed.
In fact, according to Chief Martech, cloud-first organizations today deploy a staggering 186 SaaS tech apps on average. 1 Similarly, a Ventana study found that more than one-half of sales organizations (55%) report utilizing more than 10 data sources, including one-third (33%) that use more than 20.2 And with a 2022 LXA martech survey showing over 24% of the marketing budget going to purchase new martech tools, it’s easy to see how growing amounts of customer data become fragmented and siloed.3
This presents a problem for enterprise organizations. The same LXA martech survey shows that in 2022, 57% of marketers cited inadequate integration as the main barrier to optimal use of marketing technology platforms. The answer to how to address this problem lies in data integration.
Data integration is the process of connecting fragmented, siloed data residing in different systems, standardizing it and bringing it into a central place. This enables data professionals to run analysis, unearth competitive insights and help business teams build a single view of the customer.
Because data teams are tasked with getting data and analysis to business users, they should be especially concerned with the data integration process. To find the needles of insight in the haystacks of raw data, data teams need the most optimal ways to drive the extract, transform, load (ETL) process. This means to “extract” data from multiple sources, “load” it into a single location and “transform” the fragmented, often incomplete, duplicate or incorrect data into a standardized format ready for analysis. This three-step ETL process is at the heart of data integration. You might instead run an ELT process. In the ELT process, raw data is extracted and loaded from a source to a destination data system, such as a data warehouse or data lake, and then transformed for downstream use.
With the right data integration tool for ETL or ELT, data teams can make clean and accurate data available to business teams. At the same time, they can automate data tasks and free up their own time for other work that adds value. This results in well-planned campaigns, better customer experiences and greater revenue generation supported by advanced insights, smarter predictive modeling and forecasting.
The wrong approach, however, can lead to poor decision-making that can hinder or even harm business outcomes.
Why DIY Is the Wrong Approach to Data Integration
Without a reliable tool to connect data, data analysts end up spending time creating a patchwork of pipelines and band-aid integrations to get business users the reports and insights they need. But business analysts are not software developers. So, these workarounds are often unstable and could cost the business more resources, time and effort in the long run. For enterprise business functions, DIY data integration causes technical debt, expensive reworks, disassociation from the enterprise data stack and concerns around stability, security and data governance.
Central IT could help, but often they are already stretched thin with other priorities. Depending on them to connect data and generate insights could mean delays of several weeks or even months for basic data management use cases. For data to produce actionable insights, it needs to be fresh, accurate and business-ready.
Finding the Right Data Integration Tool for Business Users Across the Enterprise
A self-serve data integration tool helps data professionals attached to business teams automate their ETL workflows without relying on central IT. A simple, smart and fast data integration tool that’s also affordable, secure and stable at any scale checks all the boxes for functional users at large enterprises.
Unfortunately, most vendors offer only some of the elements needed for easy, efficient, cost-effective and scalable ETL and ELT. Choosing a point solution can potentially result in additional challenges, especially for enterprise-scale businesses. For example:
- Marketing data integration platforms that integrate some marketing data sources but keep these in a silo, disconnected from the rest of the enterprise data.
- Data management point solutions offer only parts of the ELT or ETL process, such as data loading or transformation. They require additional vendors to complete the process, thereby adding to the complexity, cost and risk of data management.
- Marketing automation platforms offer rudimentary connectors that cannot scale with your business needs or connect to the rest of your enterprise data ecosystem.
None of these solutions can address the ETL or ELT needs of an enterprise committed to truly data-led leadership. With scale, even seemingly simple projects become complicated and costly in the long run.
Business teams within large enterprises need an end-to-end data integration solution that:
- Seamlessly connects all structured and unstructured data formats
- Support all patterns of data integration (ETL, ELT, reverse-ETL, replication, change data capture (CDC) and more)
- Ensures system stability and security at any scale
- Aligns with the enterprise data governance, even while making business users less dependent on central IT
A solution that encompasses all of these doesn’t need to be unaffordable or complex to deploy. That’s why we’ve laid out five questions below for data professionals to use to evaluate potential solutions.
5 Questions to Find the Right Solution for Your Data Loading and Transformation Needs
Ask yourself the following five questions to cut through the noise and find the right data integration solution:
1. Does the tool own all the data integration capabilities?
Not only should the solution be able to support both ETL and ELT processes for cloud data integration, but it should do so without needing that technology from third parties. Vendors who require additional partners to execute data transformation after loading can expose the business to needless risk, unpredictability, complexity and costs.
Instead, find a vendor that offers seamless, end-to-end ETL or ELT data integration capabilities within the same environment. The tool should be capable of collecting and analyzing data from diverse sources — whether on-premises, in the cloud or multi-cloud — and in different formats, without any caveats. Informatica Cloud Data Integration-Free (CDI-Free) offers connectivity to a wide range of marketing and sales applications and all major cloud data warehouses.
2. Does the tool offer speed and data freshness?
Stale data is of no use to anyone. If you have high-speed data loading from practically any data source to your cloud data warehouse, you should be able to run analytics at high speed and significantly accelerate time to value.
Many tools have a low-frequency data update cadence or impose an additional fee for a more frequent update cadence. If your enterprise business users need data in near-real-time, ensure your vendor can deliver the cadence you need, especially as data volumes scale.
Additionally, business analysts need to turn around complex data requests with speed, agility and accuracy. A tool with a variety of pre-built transformation tasks and templates helps jump-start data projects for fast and accurate results every time while automating recurring tasks. CDI-Free provides reusable mappings and templates plus incorporates proven integration techniques to automate your data pipelines.
3. What is the real cost of operations?
There are a variety of pricing and/or subscription models available across the cloud data integration vendor landscape. Some offer a short trial before locking users into a high-cost solution, whereas others raise the price after reaching a specific threshold, often as low as 500,000 rows of data. Complex pricing models aside, hidden costs can also come in the form of partner fees, the technology required for near-real-time data refresh and the DevOps resources needed for basic tasks. Organizations also face a potential loss of stability and security as workloads increase.
A quality data integration tool should require little installation, setup or DevOps time. It should also offer convenient, transparent payment options for upgrades. For example, CDI-Free has no cost or risk of unexpected expenses. If your workload exceeds 20M rows or crosses the 10-hour processing time limit per month, you can transit to the pay-as-you-go option with a single click, without the loss of data fidelity or stability. Informatica Cloud Data Integration-PayGo (CDI-PayGo) offers additional compliance support, award-winning customer support and processing of unlimited rows at a truly low cost.
4. Does the tool provide business users independence from IT?
Many vendors claim to be low-code or even no-code, so it’s important to understand what these terms mean in practice. Truly self-serve tools allow tech-savvy data professionals to get started immediately, without any help from DevOps or IT for deployment, setup or use. You should also consider the user interface. Look for point-and-click configuration and drop-down menus versus code development for commonly used functions, such as data transformations and field mapping.
CDI-Free offers a simple, wizard-driven, drag-and-drop process. This allows marketing and sales ops data professionals to add sources and join, move, validate and standardize data quickly and securely, even at scale. Contextual videos within the user environment help navigate the process and answer queries as they arise while using the tool. In-product chats provide access to a live subject matter expert to help resolve user queries in real time. With these resources, work gets done quickly and smoothly without any technical expertise required.
5. How seamlessly can the tool upgrade to more advanced versions?
Most data integration tools stumble when the data volumes increase or new data sources or targets are added or new data patterns need to be supported. At this point, you need to scale up to meet these new demands. But most free solutions become unstable, slow down or are unable to upgrade to a more full-scale solution without disruptions.
If an upgraded version is available, consider what it offers. Is it simply providing a higher data processing volume or are additional features — such as high-speed data processing, compliance protection and customer support, more sophisticated transformations, support for more sources and targets — included? Is the pricing model of the scaled-up version transparent and affordable, or will it require complicated new budgetary approvals?
CDI-PayGo offers a transparent pay-as-you-go option along with a tool to estimate and predict future usage, so you are prepared for upcoming costs. The enterprise-grade cloud data integration (CDI) offers unprecedented scale with support for 300+ connectors, executing 54 trillion transactions, and an easy-to-understand / monitor usage-based pricing model.
Choose an Easy, Efficient, Cost-Effective, Proven and Best-in-Class Solution Central IT Already Trusts
At the end of the day, data integration should simplify the entire data pipeline. This includes data loading and transformation for all marketing and sales use cases. At the same time, it needs to ensure data governance and compliance are never compromised.
Don’t be allured by solutions that can support your needs right now but will fall flat on your growth tomorrow. With Informatica CDI-Free and CDI-PayGo, you can access high-performance ETL and ELT without the risk of hidden costs, the need for expensive developers or lengthy budget approvals. And all of that comes from a name that central IT already trusts when it comes to stability, performance and data security - Informatica.