3 Things To Consider For Unified Data Success
Companies strive to unify their data because, by default, most data is inaccessible. It’s often scattered throughout the company and divided into information silos among business units and teams. Without a central way to manage data, businesses can’t make informed decisions. When companies are able to unify their data, they make all of their business units more productive. But unifying data can pose a tremendous organizational challenge, as well as an engineering one. If you feel this way – you aren’t alone. Many data professionals feel like they are “drinking water from a fire hose.” There are challenges, not only in unifying data and managing data but also generating insights from the data. The focus should be more on asking the right questions rather than seeking the best possible answers. A unified data architecture can help.
What Is Unified Data?
Unified data is when a company merges its many fragmented data sources into one, single central view. The best insights are generated not from answering one question but from answering a set of connected questions. Answering these connected questions requires using a connected set of data sources. It requires us to make a paradigm shift – from looking at each faction of data as an individual unit to viewing data from multiple sources as a single entity.
Unified data provides a more complete and accurate picture of a company’s data, but unifying the data is far from simple. To tie data sources together, companies need a system to unite them, such as an analytics platform like Neebo. Here are three things to keep in consider when starting in this field:
1. Customer-focused data strategy
A company’s data strategy should also start with the customer. A customer today has a number of touch points with the company, and the touch points continue to increase with the widespread use of technology. Customer experience is at play throughout the customer journey: while evaluating a product, during the purchase process and during consumption. Creating a 360-degree view of the customer therefore is the first step in the journey toward providing a better customer experience.
Companies will need to quickly start looking at the benefits of exploring and utilizing multiple data sources to achieve business outcomes. Companies need to look inside as well as outside at the data sources that are freely available or purchased externally. They need to look at exploring and working with large amounts of unstructured data – which can be difficult to process and analyze. They also need to keep the customer at the center of their data strategy so that customer experience is the best possible.
2. Integration of unstructured and structured data
Integrating structured and unstructured data is one of the most important tasks required to run unified analytics. Structured data from transactional systems enable understanding of what a customer is doing. Unstructured data from sources like blogs, videos, discussion forums and call center discussions allow businesses to understand what a customer is thinking and feeling.
Looking at these data sources in an integrated manner creates an important link between “what the customer is thinking” and “what the customer is doing.” Any analysis done using integrated data would have far higher quality of insights than doing analysis on either of these sources alone.
3. Look beyond traditional sources
Organizations have traditionally looked at utilizing data from within. However, there is a wealth of information available by purchasing not only 3rd party data, but also public data sets. Imagine a clothing retailer attempting to determine whether to put a summer clothing line on sale. The retailer can purchase 3rd party weather data and accurately estimate when it would not be warm enough for summer clothing. That information can be used to determine the sales expected, which would help determine inventory.
There is also plenty of data openly accessible. Macroeconomic data for most of the world is available from the United Nations websites, the U.S. census information is available for download online, and 500 million tweets per day are available for analysis. As I’ve written previously, this mostly free data is also very valuable to enterprises if leveraged optimally and in real time.
The number and diversity of data sources is going to continue to expand as organizations migrate their data to cloud data warehouses like Snowflake, Azure, and Redshift. (For more info, see my comparison of Snowflake & Redshift.) There may be many other data sources we cannot imagine today but will become a reality very soon.
How can analytics platforms help with unified data?
Emerging analytics platforms, like Neebo, are purpose-built to capture and analyze data from a variety of sources. They are, by definition, tools for unifying data. Most offer pre-built integrations to common systems and universal APIs for less common ones. They allow enterprises to tie their ERP, CRM, web applications, marketing systems, customer applications, and data partners together to view the data from one interface.
What should you look for in an analytics platform?
The best analytics platforms have highly intuitive interfaces that are designed to mask the complexity of the underlying data architecture. They use dashboards to help users visualize their data. Neebo features machine learning algorithms to simplify and automate the process of analysis. Brands can use an analytics platform to knit data from across silos, business units, and teams together and provide everyone access. Because the more individuals within a business that are data-informed, the better.
See how you can unify and add third-party assets in Neebo’s product demo. By adding and tagging these within Neebo’s Analytics Hub, your entire team can share and utilize these great assets all from one place.