Alation offers enterprise data intelligence solutions, including data search & discovery, data governance, data stewardship, analytics, and digital transformation. Alation operates in thethe data catalog market. With its Behavioral Analysis Engine, inbuilt collaboration capabilities, and open interfaces, Alation combines machine learning with human insight with the goal of tackle the most demanding challenges in data and metadata management.
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Parse.ly
Score 7.8 out of 10
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Parse.ly is a content optimization platform for online publishers. It provides in-depth analytics and helps maximize the performance of the digital content. It features a dashboard geared for editorial and business staff and an API that can be used by a product team to create personalized or contextual experiences on a website.
Alation is well suited to helping a user find a column or even a query using a business term search. In this regard Alation is excellent because it's easy to not only associate these items with each other, but there are also many ways to link the column and/or query to that business term/concept
Parse.ly is a great tool for publishers who want to track engagement and audience behaviour across websites. With Parse.ly, we can easily track metrics like pageviews, time spent on page, and scroll depth to see which content is resonating with our audience and optimize our content strategy accordingly. Our marketers found Parse.ly to be an excellent tool for tracking the effectiveness of our campaigns. We can use Parse.ly to track metrics like referral sources, conversion rates, and engagement by audience segment to see which channels and tactics are driving the most engagement and conversions.
Ability to link objects using the @ symbol. It allows us to easily provide a way to get more information or context. So if the business concept is part of a hierarchy, we can link to the other terms in that hierarchy.
The customization is really helpful. Most object types have robust customization options. Others are less so, but it is improving. We've created multiple custom fields to support our data governance framework.
The search feature with filtering is helpful in narrowing down what you're looking for.
The lineage UI is not ready for primetime. I would not recommend this feature for my users at this time because it's too complex to understand and is visually difficult to track down specific paths.
The underlying infrastructure of the on-premise version of the software is fragile and unnecessarily complicated, using too many modules and technologies.
The license model of the on-premise version contains too many add-ons. I would like to pay one price and get all of the features.
Overall, we are happy with the functionality of the platform. While there are are areas that we would like to see further improvement in, the tooling is highly configurable and aligns well with our use case. A mature API layer makes it straightforward to integrate with other data tooling. Alation stands out for its pro-active engagement with their customers, both to resolve issues and in communicating their feature roadmap
As an employee, this is difficult for me to comment as I am not directly funding or making these business decisions. However, it is a tool many get on with for surface level data that is useful to editorial teams.
Mostly because the search feature is case sensitive. This causes issues when users are searching for an industry standard acronym. These acronyms exist as attributes in thousands of places across our data ecosystem. Alation allows stewards to endorse attributes so that these endorsed items rise to the top of search results. The problem is no one types acronyms in caps in a search field. Alation returns results matching the case (lower-case) and in several instances the endorsed attributes don't even appear on the first page of results
The Parse.ly platform is very user-friendly and easy to use. User management is simple, and reporting setup only takes a few minutes. They provide very helpful documentation for implementing the scripts on your site and have great customer support to help with custom development such as implementing their content recommendation engine.
The account management and technical support teams are both excellent. There is regular account manager engagement, and technical issues are generally resolved very quickly. The vendor engages us in product development through regular updates on the product strategy & feature roadmap.
I rate this question this way solely because I haven't requested any support. I feel where I will eventually get support would be when we take Parse.ly up on some training that is being offered. We are looking to do that at some point after the first of the year and when our schedules support it.
Key insight from implementing Alation is that, as a cloud-based SaaS product, the majority of effort is not infrastructure-related but instead focused on security configuration and integration with existing platforms, including identity management, access controls, and metadata connectivity to core data systems. Because of its data profiling functionality, careful consideration had to be given to data security and data sovereignty.
Alation provided the right balance of connection with systems in use, trusted reputation and affordability. The product integrates with current ways of working and does not require reorganisation within other lines of business.
Parse.ly does pretty well compared to Chartbeat, particularly when it comes to historical information and analysis options that are easy for employees to use after some short training. The onboarding for Parse.ly is intuitive, and the scheduled reports take away basically all of the inconvenience associated with regular metrics reviewing. But Chartbeat wins in its social audience tracking because it can source traffic to a specific social post, which can show you exactly how your audience is coming to your content and where you need to put your content to be sure you get that audience.
Provides a place where people can go to find things
When we first implemented, someone was concerned that people would now see what a mess our data environment was. I consider that a feature. We can't clean up if we can't see what we have.
Sometimes in meetings our editorial director will point out stories that didn't perform well. To us, that means readers don't really care about the topic, so we'll pivot away from writing about that in the future. That might not be "business objectives" though.
