Likelihood to Recommend Datameer is a great tool if someone is capable of keeping the most recent version of the tool up to date along with the most recent version of the distribution of Hadoop. The tool is easy to support but it must have someone who can run the back end processes
Read full review Quick dashboards from
Google Sheets - Easier to do the graphs than in
Google Sheets - Operational dashboards to be used in the day-to-day work - It is good both for retrospective data and to do a pulse check of the current status - Better for not giant amounts of data and not multiple data sources. - If you need a lot of graphs to be displayed on the same page, it can be a bit glitchy during configuration (then the use works fine).
Read full review Pros It leverages scalability, flexibility and cost-effectiveness of hadoop to deliver an end-user focused analytic platform for big data without involvement of IT. It overcomes Hadoop`s complexity by providing GUI interface with pre-built functions across integration, analytics and data visualization . Excel feature is awesome for business users which is already provided by Datameer. Using datameer now user can do smart analytic using Decision Trees, Column dependency and recommendation. Recently HTML5 inclusion is making application to available on a wider range of devices, including the iPad and other mobile devices which does not support Flash. It can be used in premise or in a cloud computing environment. Wizard-based data integration designed for IT and business users to schedule and do transformation of large sets of structured, semi-structured and unstructured data without any knowledge of Hadoop ecosystem. Read full review Filtering - you can filter across different dimensions and metrics to get a more specific "cut" of data Refreshing - data automatically ingests into Looker which allows reports to be updated and backfilled in real time Conditional Reporting - you can leverage Looker's reporting features to flag when a given metric or KPI falls below or above a specified threshold. For example, if you had a daily sales benchmark in a SAAS organization, you could use Looker to flag whenever daily sales falls above or below the benchmark Read full review Cons Concentration issues are possible while using a lot of tabs at once. In most cases, the length of a tutorial video is excessive. A more condensed design is certainly a viable option. Read full review Looker is less graphical or pictorial which makes it less attractive Consumes a lot of memory when there are multiple rows and columns, impacts performance too At times when we download huge chunks of raw data from Looker dashbords, the time taken to prepare the file is enormous - The user fails to understand if Looker has frozen or if the data is getting prepared in the background for downloading. In turn, user ends up triggering multiple downloads Read full review Likelihood to Renew Employees with intermediate SQL and Hive knowledge can generate reports faster than using Datameer . It does have visualization tool but I don't think it is anything that cannot be accomplished by importing the data in Excel
Read full review We've been very happy with Looker so far, and all teams in the organization are starting to see its value, and use it on a frequent basis. It has quickly become our accessible "source of truth" for all data/metrics.
Read full review Usability Easy to use for most things, starts to require some planning as your projects get more complex.
Mike Blizman Administration of Hadoop cluster - Cloudera, Datameer
Read full review Looker is relatively easy to use, even as it is set up. The customers for the front-end only have issues with the initial setup for looker ml creations. Other "looks" are relatively easy to set up, depending on the ETL and the data which is coming into Looker on a regular basis.
Read full review Support Rating Never had to work with support for issues. Any questions we had, they would respond promptly and clearly. The one-time setup was easy, by reading documentation. If the feature is not supported, they will add a feature request. In this case, LDAP support was requested over OKTA. They are looking into it.
Read full review Alternatives Considered Pricing, support, and ease of use. We plan to scale up our data over the net few years and Datameer gives us all the things we need in one tool. Handles large transformations quickly and works with all the cloud data warehouses.
Datameer's per-user pricing sealed the deal for us as we plan to transfer much more data over the next few years. We looked at
Fivetran but the usage pricing discourages growth. We also looked at Informatica but it was too expensive and didn't work as well with other BI tools like Datameer does.
Read full review Looker is an off-the-shelf, free tool for Google business users. Other than the internal cost of time to build, we had no costs to set up what we needed to do. Knowledge sharing internally and using templates greatly reduced this cost, making the overall cost very low.
Read full review Return on Investment We have not been able to reach our business objectives just yet. Hadoop its a hard sell in most companies still. Legacy skills are still highly on demand and as long as an easier path leverage SQL for example is available, it would be hard to gain more adoption. Read full review Allowing others to self-serve their own analytics and connect it to Looker simply and easily has helped unblock the central data team so they can instead focus on validated dashboards whilst stakeholders manage their day-to-day analysis themselves. Countless engineering hours have been freed up by not having to manage every user permission for each BI tool; we have a BYOBI approach; Bring Your Own BI Creation and management of a semantic layer (LookML =Looker Modeling Language ) allows peoples sandboxes and production databases to become clutter free. Minor adjustments, conditional fields, and even some modelling can all be done in LookML which doesn't need oversight or governance from the central data team. LookML, specifying drilldown fields and their sub-queries, as well as generally creating dynamic parameters with Liquid are all great features, but can have a steep learning curve. it may take some time to understand how to create this middle layer correctly, or even pose a risk of inheriting complex code from another source which can be unmaintainable if it becomes too big. Some level of governance is recommended if Looker is used by a large number of editors. Read full review ScreenShots