Monthly Archives

February 2019

Microsoft Lead Gartner 2019 Magic Quadrant for Analytics and BI

By | Data Visualisation | No Comments

Hot BI news is the recently announced 2019 Gartner Magic Quadrant for Analytics and BI and Microsoft was the clear leader, driven in part without doubt by the explosive growth of PowerBI .

2019 Gartner Magic Quadrant BI & Analytics

2019 Gartner Magic Quadrant BI & Analytics

PowerBI is the story

PowerBI is advancing at a rate which its key competitors – Qlik & Tableau – are struggling to match. Further underpinning Microsoft’s lead is its ongoing investment in the underlying Azure Data & Analytics Platforms which give it an edge that competitors just can’t match.

One thing I am frequently hearing from the market is that other platforms are struggling to match PowerBI’s compelling price point – some might cynically say Microsoft are using their deep pockets to undercut everyone else. However in a recent conversation I had with a long standing Cognos customer, once they understood what the product could do – and how much cheaper and faster it would be – it drove them to reconsider their strategy.

I freely admit was initially cynical about Self Service BI a few years ago as it rapidly became transparent that for all the slickness of creating great looking reports the tools were still beholden to a clean set of well managed data. Now modern data platforms are reducing the cost and complexity of providing this data, I am now holding the position that self service BI can really deliver on its value rather than just provide a final polish to a Data Warehouse – as long as it is paired with such a platform.

I continue to maintain my (unpopular in some circles) position that Qlik has nothing unique to offer any more and is doomed to irrelevance unless it innovates or at the very least catches up with its competitors. Tableau remains a solid tool for self service analytics, but the absence of an underlying data platform is going to start hurting it before too long. I would expect it’s longevity to be tied to being acquired by someone suitably huge.

I also note the absence of any serious competition from the other two cloud megavendors. Google offers Data Studio & Amazon has Quicksight – but neither rate a mention. I would watch this space carefully as the pace of innovation by both companies is fierce and Google in particular has strong AI / ML capabilities. Both are also ramping up their own data platform services.

Outside the Big 3

If you are on any of the legacy on premise tools in the 2019 Gartner Magic Quadrant for Analytics and BI such as Cognos/IBM, Oracle or SAS then i’d be seriously considering where you go next. The pace of innovation in the cloud is hard to ignore and users risk lagging behind their competitors if they cling to these.

SAP and Salesforce have a strong story within their own source but have their weakness in using data from outside the native platform. Doing anything in SAP is horribly expensive, and my conversations with Salesforce BI users have not left a very positive impression of the tools’ capabilities.

The remainder either are strong in their niches and / or have minimal presence in Australia (Microstrategy is basically unsupported here as there’s no people doing it) so i’ll not pass comment on them.

Where to from here?

If you have reviewed the 2019 Gartner Magic Quadrant for Analytics and BI and decided you want to know more about PowerBI and the Microsoft Data Platform, we can help.

Full disclosure – FTS Data & AI are a Microsoft Gold Partner so this post is a bit biased. However if you are not using PowerBI and are looking at migrating to a more cost effective platform, want to understand how cloud capabilities are transforming data and analytics – or work for Qlik and want to lure me into a dark alley – please contact us.

FTS Data & AI are Microsoft Gold Partners Data Analytics

Microsoft Gold Partners Data Analytics

 

SSIS Integration Runtime Connectivity Testing

By | Data Platform | No Comments

SSIS Integration Runtime Connectivity Testing is hard as there is no physical Azure VM to log in to as part of the Azure Data Factory (ADF). While behind the scenes there is effectively a VM spun up there is no way to access it.

The scenario our Data Platform team faced was reasonably simple – we needed to connect to a 4D database that sat behind the Storman application that our customer used so that we could extract data for their various workloads. Because 4D is not supported by the Generic ODBC source in Azure Data Factory, we needed to use the 4D ODBC driver. This meant using SSIS to leverage the driver.

The client is well managed in terms of security so the target system can only be accessed within their network. Their Azure network was connected to theirs and properly secured, so part of the setup of the SSIS Integration Runtime in Azure Data Factory is to ensure that it is joined to the virtual network.

Houston, we have a problem

SSIS Azure Data Factory

SSIS Azure Data Factory

However, despite all this – we couldn’t get the ODBC connection to work when deployed. Due to stability issues our first suspect was the driver – after all it frequently crashed Visual Studio 2017 / SSDT and configuration was a pain. Also, initially we couldn’t connect on our dev machines as we weren’t on the clients VPN (easily fixed, fortunately). Then we had the wrong target server (again easily fixed).

Once we got on to ADF of course our debugging options got more limited as we now were having to do SSIS Integration Runtime Connectivity Testing without all the tools available on our desktops . Initially we struggled because the runtime was very slow at sharing its metadata (package paths, connection managers, etc.) so we weren’t initially sure it was even able to work with the driver. Eventually we got enough metadata to start playing with the JSON of the task to configure it. However we continued to get errors in ADF that were’t really helping.

Our breakthrough came when we remembered we could just connect to the more familiar and mature environment of the SSIS catalog that is deployed alongside the runtime. We configured the package correctly, ran it and got a more manageable ODBC error – “Cannot reach Destination server”. A quick ping from our desktops proved the server could be pinged, so as a test we used a simple package with just a script task to ping the server. This worked just fine on our desktop, but when deployed the script task reported failure.

So a quick connectivity test helped pin it down to probable network config issue. Now it’s in the Infrastructure teams hands to ensure everything is configured correctly, but at least we have (for now at least) got SSIS & the ODBC driver off the list of probable causes of the issue. It’s also taught us a few things about SSIS Integration Runtime Connectivity Testing.