Increasing importance of analytics an opportunity for ISVs
With more organizations looking to data to inform decision-making, there's a growing need for the services of independent software vendors and data providers.
With analytics becoming a requirement rather than a luxury as organizations navigate constantly changing economic conditions, an opportunity opens for ISVs (independent software vendors) to grab market share.
Data is becoming the fuel for business, the basis for the informed decision-making that enables organizations to act and react quickly as worldwide events like the COVID-19 pandemic and the war in Ukraine create economic instability, according to David Menninger, an analyst at Ventana Research.
"The world is changing, and data has become a huge opportunity," Menninger said on June 8 during a webinar hosted by analytics vendor Qlik. "You could say it's the new oil, or it's the new black, or it's the new water. It's clear that today the world runs on data, and if [organizations] are not taking advantage of the data that they're collecting, they're going to be at a competitive disadvantage."
New opportunities
Harnessing data and making it actionable, however, is not simple, and many organizations don't have the personnel or expertise do so.
They need outside help to ensure that their systems ingest data in an organized way, integrate data from multiple sources, cleanse and catalog it to make sure its quality is high and it's organized, and prepare data for analysis so organizations can make data-informed decisions.
And that's where the opportunity lies for ISVs.
David Menninger, an analyst at Ventana Research, speaks during a webinar hosted by analytics vendor Qlik. Also pictured are Qlik's Joe Gabriel (bottom left) and Dan Potter.
ISVs can be large, independent vendors like Qlik, MicroStrategy and SAS, but often they are third-party vendors that use some of the tools provided by those larger platform vendors, add their own expertise to build new products using the tools, and then package them and sell them as their own products or customize products for their clients.
It's clear that today the world runs on data, and if [organizations] are not taking advantage of the data that they're collecting, they're going to be at a competitive disadvantage.
David MenningerAnalyst, Ventana Research
So when organizations struggle with different aspects of the analytics pipeline, anything from data ingestion through analysis and insight, ISVs can provide technology and expertise that enables those organizations to address their problems and make their data actionable.
"ISVs can help tackle these challenges and can be very valuable to the organizations they're dealing with," Menninger said.
One of the key things ISVs can do to assist organizations is automate complex or time-consuming processes, according to Dan Potter, vice president of product marketing at Qlik.
Data preparation, in particular, is both complex and time-consuming and ripe for automation.
Data quality is critical -- when poor data is used to make decisions, the results can be disastrous -- so business IT teams need to look at each data point to make sure it's correct.
Organizations, however, collect copious amounts of data points daily -- with most things an organization does serving as a data point -- so to manually examine each transaction or click of a webpage view or step on a supply chain would be nearly impossible.
And the amount of data organizations collect is only growing. In 2010, the worldwide volume of data created, captured, copied and consumed was two zettabytes, according to Statista. By 2020, it was 64.2 zettabytes, and by 2025 it's expected to grow to 181 zettabytes -- a 90-fold increase over 15 years.
By automating data preparation, organizations eliminate some of the friction associated with it, and ISVs can provide both the technology and expertise to automate the data preparation process.
"We're still in a situation where data preparation is a huge issue," Potter said. "It's been this way for over 20 years -- as long as there have been analytics tools, people have struggled with data preparation. What we need to do is get 95% of the data into operational pipelines … to handle the vast majority of this. From a technology perspective, there's no reason organizations should [struggle]."
Governance and AI
Other areas in which ISVs can be of particular assistance to organizations struggling with their data are data governance and the use of augmented intelligence and machine learning to go beyond descriptive analytics about what happened to predictive and prescriptive analytics to examine what might happen next and what to do if and when that happens.
Data governance is a vital aspect of analytics, both to keep organizations from violating regulations and to foster safe and secure self-service data exploration that can lead to growth.
ISVs can help organizations develop data governance frameworks and put safeguards about how to use and who can use data in place, and they can also assist in securing the movement of data -- with spreadsheets, in particular, a notably leaky format -- that can sometimes expose sensitive data and result in breaches.
"The ability to make data governance a value-add in the eyes of data consumers is important," Potter said. "When they understand there are policies in place to protect themselves for the use of data, that's very important."
He added that data lineage is an area in which ISVs can assist organizations, enabling them to see where their data came from and how it's been used, to increase the trust in their data.
"Trust comes from transparency and understanding," Potter said. "If the business user is looking at a data set and they can understand where it came from, how it was transformed along the way, by whom and when, and who else uses this data, that can help inspire trust and confidence."
Meanwhile, using AI and machine learning is complicated, usually requiring the skills of a trained data scientist.
Large organizations have the resources to hire teams of data scientists to build and operationalize AI and machine learning models. But many small and midsize companies, most nonprofit organizations and even some government agencies don't have the financial means to bring on dedicated data scientists.
ISVs, however, can step in and be a resource for such organizations.
Beyond enabling organizations to access and prepare data for advanced analysis, they can provide skills.
"Organizations don't have enough skilled resources, so ISVs may be in a better position to create some of those analyses than their customers," Menninger said. "But whether they're doing the AI and [machine learning] or not, helping organizations access the data and make it available for those analyses is still an opportunity."
Data providers
In addition to ISVs, the increasing importance of data presents a new opportunity for data providers to expand their reach.
While internal data helps organizations understand how outside factors and internal decisions influence them, external data can add context. For example, external data can help organizations understand why there was a disruption in their supply chain or sales suddenly went up or down during a particular season when in the past sales held steady.
Data providers, including big ones such as Experian and Dun & Bradstreet, among others, can help equip organizations with that additional data needed to improve their analysis.
"Organizations have embraced external data, and external data has a positive correlation with outcomes in organizations," Menninger said. "It's important for organizations to take advantage of all the information that's available to them."
Beyond just providing organizations with more data sources, data providers can assist organizations in some of the same ways as ISVs. Using their expertise, data providers can help organizations integrate data from multiple sources, catalog and govern data and keep their data up to date, according to Menninger.
Unlike the ISVs, however, data providers can help not by developing technologies to integrate data or govern it, but by packaging it and delivering in a way that makes it easy for customers to manage and use.
"Delivering data in a way that organizations can consume is an important element of helping them take advantage of it," Menninger said. "You want to make [their processes] easier."
