The growing importance of analytics is an opportunity for ISVs

With analytics becoming a requirement rather than a luxury as organizations navigate ever-changing economic conditions, an opportunity is opening up for ISVs (Independent Software Vendors) to capture market share.

According to David Menninger, analyst at Ventana Research.

“The world is changing and data has become a huge opportunity,” Menninger said June 8 during a webinar hosted by analytics provider 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] don’t take advantage of the data they collect, they will be at a competitive disadvantage. »

New opportunities

However, harnessing data and making it actionable isn’t straightforward, and many organizations don’t have the people or expertise to do so.

They need outside help to ensure their systems ingest data in an organized way, integrate data from multiple sources, cleanse and catalog it to ensure high quality and organized , and prepare data for analysis so that organizations can make data-driven decisions. .

And therein lies the opportunity for ISVs.

Ventana Research analyst David Menninger speaks during a webinar hosted by analytics provider Qlik. Also pictured are Joe Gabriel (bottom left) and Qlik’s Dan Potter.

ISVs can be large independent vendors such as Qlik, MicroStrategy, and SAS, but they are often third-party vendors who use some of the tools provided by these large platform vendors, add their own expertise to create new products to using the tools, then package sell them as their own products or customize products for their customers.

For example, many ISVs use the built-in analytics capabilities of Logi Analytics to create their own embeddable applications that can be customized and sold to customers.

It is clear that today the world runs on data, and if [organizations] don’t take advantage of the data they collect, they will be at a competitive disadvantage.

David MenningerAnalyst, Ventana Research

So when organizations grapple with different aspects of the analytics pipeline, from data ingestion to analytics and insight, ISVs can provide technology and expertise that enables those organizations to solve their problems and to make their data usable.

“ISVs can help address these challenges and can be invaluable to the organizations they deal with,” Menninger said.

According to Dan Potter, VP of Product Marketing at Qlik, one of the main things ISVs can do to help organizations is automate complex or time-consuming processes.

Data preparation, in particular, is both complex and time-consuming and ripe for automation.

Data quality is critical – when poor quality data is used to make decisions, the results can be disastrous – so enterprise IT teams need to examine every data point to ensure it is correct.

Organizations, however, collect vast amounts of data points on a daily basis – most things an organization does serving as a data point – so manually reviewing every transaction or click of a web page view or step on a chain of data. supply would be almost impossible.

And the amount of data that organizations collect is only increasing. In 2010, the global volume of data created, captured, copied and consumed was two zettabytes, according to Statista. In 2020 it was 64.2 zettabytes and by 2025 it is expected to reach 181 zettabytes, a 90-fold increase in 15 years.

By automating data preparation, organizations eliminate some of the friction associated with it, and ISVs can provide both the technology and expertise needed to automate the data preparation process.

“We’re still in a situation where data preparation is a huge issue,” Potter said. “It’s been like this for over 20 years – as long as there have been analytics tools, people have struggled with data preparation. What we need to do is put 95% of the data into operational pipelines…to handle the vast majority of that.From a technology perspective, there’s no reason for organizations to [struggle].”

Governance and AI

Other areas where ISVs can be particularly helpful to organizations struggling with their data are data governance and the use of augmented intelligence and machine learning to go beyond descriptive analytics on what happened to predictive and prescriptive analytics to examine what might happen next and what to do. do if and when it happens.

Data governance is a critical aspect of analytics, both to prevent organizations from violating regulations and to enable safe and secure self-service data exploration that can drive growth.

ISVs can help organizations develop data governance frameworks and put safeguards in place for how and who can use data, and they can also help secure the movement of data – with data sheets. calculation, in particular, a particularly leaky format – which can sometimes expose sensitive data and lead to breaches.

“The ability to make data governance add value in the eyes of data consumers is important,” Potter said. “When they understand that there are policies in place to protect themselves from the use of data, that’s very important.”

He added that data lineage is an area where ISVs can help organizations, allowing them to see where their data came from and how it was used, in order to increase trust in their data.

“Trust comes from transparency and understanding,” Potter said. “If the business user looks at a set of data and can understand where it came from, how it has been transformed along the way, by whom and when, and who else is using that data, that can help to inspire confidence.”

Meanwhile, using AI and machine learning is complicated and usually requires the skills of a skilled 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 medium-sized businesses, most nonprofits, and even some government agencies don’t have the financial means to hire dedicated data scientists.

ISVs, however, can step in and be a resource for these organizations.

In addition to enabling organizations to access data and prepare it 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 these analyzes than their customers,” Menninger said. “But let them do the AI ​​and [machine learning] or not, helping organizations access data and make it available for these analyzes remains an opportunity.”

Data providers

In addition to ISVs, the growing importance of data presents a new opportunity for data providers to expand their reach.

While internal data helps organizations understand how external factors and internal decisions influence them, external data can add context. For example, external data can help organizations understand why there was an interruption in their supply chain or why sales suddenly increased or decreased during a particular season when in the past sales were remained stable.

Data providers, including big ones like Experian and Dun & Bradstreet, among others, can help equip organizations with the additional data needed to improve their analytics.

“Organizations have embraced external data, and external data has a positive correlation with outcomes in organizations,” Menninger said. “It is important that organizations take advantage of all the information that is available to them.”

In addition to providing organizations with more sources of data, data providers can help organizations in the same way ISVs can. With their expertise, data providers can help organizations integrate data from multiple sources, catalog and govern data, and keep their data fresh, according to Menninger.

Unlike ISVs, however, data providers can help not by developing technologies to integrate or govern data, but by packaging and delivering it in such a way that it is easy for users to manage and use. clients.

“Providing data in a way that organizations can consume is an important part of helping them leverage it,” Menninger said. “You want to do [their processes] Easier.”

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