Many businesses are learning how to use the data they generate, as well as commercially available third-party data sources, to create a competitive advantage through data analytics. But as the volume of data soars, several challenges emerge, not all of them technical.
More Data to Analyze Means More Data to Manage
Just because everyone knows that data volumes are growing by leaps and bounds doesn’t mean data management is not a challenge. An IDC whitepaper published in 2018 predicts that “the collective sum of the world’s data will grow from 33 zettabytes this year (2018) to a 175ZB by 2025, for a compound annual growth rate of 61 percent.” Who knows what a zettabyte is? A trillion gigabytes. If the prediction is off by a few ZBs, does it matter? Not really; point taken.
Moreover, much of the data is unstructured or semi-structured, which is harder and messier to manage. The results of a SharePost survey published in Forbes found that more than 95 percent of businesses face the need to manage unstructured data, with over 40 percent saying they must do so on a frequent basis.
Finally, more data means more poor-quality data and more data formats to accommodate.
As Data Environments Evolve, Industry Borders Dissolve
Amazon opened for business in 1995 as an online bookstore. Now it’s hard to think of a product you can’t buy via Amazon. But this sector-busting trend is hardly limited to Amazon. Now you can book airline flights through Airbnb. Energy drink dominant Red Bull has expanded into TV shows, magazines, books, and other media. Uber branched into food delivery. Tesla added electricity storage for the home.
“By creating a customer-centric, unified value proposition that extends beyond what end-users could previously obtain (or, at least, could obtain almost instantly from one interface), digital pioneers are bridging the openings along the value chain, reducing customers’ costs, providing them with new experiences, and whetting their appetites for more.” — Analytics Comes of Age
What’s driving all this rebellious sector hopping — and giving traditional industry stalwarts the heebie-jeebies? Data and data analytics.
The recording from the March 19 live webinar "Discover, Understand, and Integrate Your Data for Better Outcomes" will be available soon.
Business Data Environments are Evolving
As industry borders dissolve in favor of digital commercial ecosystems that can meet rising consumer expectations, the trend gains momentum from businesses that have unfettered access to critical data hosted in the cloud and in legacy on-premises systems. These ecosystems use data to "connect the dots" — often predicting consumer demands before they emerge. Paraphrasing Steve Jobs, people often don't know what they want until they see it.
Multi-cloud data movement and streamlined data access across the enterprise and within a digital ecosystem puts added pressure on the IT team and increases their data management responsibilities. And security, privacy, and data governance in a hybrid environment are only a piece of the many things IT is tasked with managing.
Adding complexity to the situation are data regulations such the European Union's General Data Protection Regulation (GDPR) and the desire it has unleashed for “data liberation.” Briefly, data liberation is the practice of allowing users to view and export the data you have about them. Data liberation is becoming a common requirement for sophisticated consumers and businesses purchasing a service that stores their data externally.
What are the Barriers to Using Data Efficiently and Effectively?
People responsible for managing data and getting answers from it, such as data engineers and data scientists, spend a lot of their time finding and preparing data — as much as 80 percent — rather than analyzing it. This is the decades old Extract, Transform, Load (ETL) dilemma. Prepping an ETL project can consume an inordinate chunk of time and resources for the typical business intelligence (BI) project.
Citizen data scientists (business analysts) are in an even tougher spot. They often need help from IT to find and prepare data, which can take weeks. Plus, the quality of the analysis depends on the quality of the data, which is often subpar due to time constraints. That quality increases when analysts can find and use the best data sets instead of those that are simply the easiest to find.
Becoming a Data-Driven Organization
Businesses that want to survive know they need to transform themselves into data-driven organizations. And they want to extract maximum value from the massive amounts of data they’re generating as well as historical data. But to become truly data-driven, organizations need to:
- Help all employees quickly find the right data for each situation and analysis
- Support collaboration between analytically savvy and technologically naïve users
- Share knowledge about data throughout the organization — regardless of the varied skill levels within the business user community
Boomi Can Help You Find, Catalog, and Prepare Your Data
At Boomi, as we worked with our customers on their data journeys, we realized that customers struggled with "dark data" — data acquired but not used — across their enterprises. Yet once they resolved this problem, the next problem arose: integrating this data with other known data stores.
To help customers unite disparate data regardless of where it resides, we needed to extend the capability of our platform. That’s why we acquired Unifi Software in 2020. Unifi's comprehensive suite of self-service data discovery and preparation tools are now part of the Boomi iPaaS — Boomi Data Catalog and Preparation.
With Boomi Data Catalog and Preparation, all your data stores appear as one, and you can view and access that data easily, no matter where it resides: in the cloud of your choice, file systems, an on-premises database, or a data lake.
Boomi Catalog provides a centralized, collaborative environment to encourage exploration for technical and non-technical users. They can overcome the challenges of data silos, immature tools, rapid data growth, and redundant data to answer critical questions such as:
- What data sets have the highest quality data?
- Has analysis already been done for a business problem?
- What data sets are accessed most often?
- Which systems contain data from domains of interest (for example, regulatory with personally identifiable information (PII)).
But that’s just the beginning. Boomi Data Preparation takes a radically different approach to data preparation. Instead of legacy ETL tools, you get a prescriptive process that automates many of the steps a user must take to cleanse, enrich, parse, normalize, transform, filter, and format data prior to visualization.
Boomi Data Preparation is powered by proprietary AI capabilities that continuously learn patterns in the data your users are profiling and register every single user selection. And the results are delivered to users via natural language processing, so technical and business users alike can “talk” to their data in a Google-like query experience that truly democratizes data access and analysis.
Data is Like Air
Everything we do — individually and as organizations — generates data. Gobs of it. It is quite literally the air organizations must breathe if they’re to succeed in the digital economy. And the digital economy is quite rapidly becoming simply the economy.
The new Boomi Platform capabilities — Data Catalog and Preparation — offer self-service data discovery, cataloging, and preparation tools that empower business users, regardless of their technical competence, to achieve deeper insights, faster.
To learn more — and breathe easy — watch our webinar "Discover, Understand, and Integrate Your Data for Better Outcomes" (recording coming soon).
About the AuthorFollow on Twitter Follow on Linkedin More Content by Thameem Khan