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Planning Analytics for Excel: Trace TI status

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2 min

IBM has been recommending its users to move to Planning Analytics for Excel (PAX) from TM1 Perspective and/or from TM1 Web. This blog is dedicated to clients who have either recently adopted PAX or contemplating too and sharing steps on how to trace/watch TI process status while running process using Planning Analytics for Excel. Steps below should be followed to run processes and to check TI ...

IBM has been recommending its users to move to Planning Analytics for Excel (PAX) from TM1 Perspective and/or from TM1 Web. This blog is dedicated to clients who have either recently adopted PAX or contemplating too and sharing steps on how to trace/watch TI process status while running process using Planning Analytics for Excel.

Steps below should be followed to run processes and to check TI process status.

1. Once you connect to Planning Analytics for Excel, you will be able to see cubes on the right-hand side, else you may need to click on Task Pane.

 
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2. Click on the middle icon as shown below and click on Show process. This will help show all process (to which respective user has access to) in Task Pane.

 
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3. You will now be able to see Process.

 

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4. To check/ trace status of the process (when triggered via Planning analytics for excel) right-Click on Processes and click Active processes.

 

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5. A new box will pop-up as shown below.

 
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6. You can now run process from Task pane and check if you can track status in new box popped up in step 5.

 

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7. You can now see the status of process in this box, below is a screen print that shows the for-process cub.price.load.data, process completed 4 tasks out of 5 tasks.

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8. Below screen prints tells us if the status of TI process, they are Working , Completed and Process completed with Errors.

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Once done, your should be able to to trace TI status in Planning Analytics for Excel. Happy Transitioning.

As I pen down my last Blog for 2019, wishing you and your dear ones a prosperous and healthy 2020.

Until next time....keep planning & executing.

 

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Planning Analytics Audit log – Little known pitfall

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2 min

The blogs brief about the challenge faced post enabling the Audit log in one of our client's environment. Once the audit log was turned on to capture the metadata changes, the Data Directory backup scheduled process started to fail.

After some investigation, I found the cause was the temp file (i.e., tm1rawstore.<TimeStamp> ) generated by the audit log by default and placed in the data directory.

The Temp file is used by audit log to record the events before moving it to a permanent file (i.e., tm1auditstore<TimeStamp>). Sometimes, you may even notice dimension related files (i.e., DimensionName.dim.<Timestamp>), and these files are generated by audit log to capture the dimension related changes.

The RawStoreDirectory is a tm1.cfg parameter related to the audit log, which helped us resolve the issue. This parameter is used to define the folder path for temporary, unprocessed log files specific to the audit log, i.e., tm1rawstore.<TimeStamp>, DimensionName.dim.<Timestamp>. If this Config is not set, then by default, these files get placed in Data Directory.

RawStoreDirectory = <Folderpath>

 

Now, let's also see other config parameters related to the audit logs

 

AuditLogMaxFileSize:

The config parameter can be used to control the maximum size audit log file to be before the file gets saved and a new file is created. The unit needs to be appended at the end of the value defined ( KB, MB, GB), and Minimum is 1KB and Maximum is 2GB; if this is not specified in the TM1 Cfg then the default value would be 100 MB.

AuditLogMaxFileSize=100 MB

 

AuditLogMaxQueryMemory:

The config parameter can be used to control maximum memory the TM1 server can use for running audit log query and retrieving the set. The unit needs to be appended at the end of the value defined ( KB, MB, GB) and Minimum is 1KB and Maximum is 2GB; if this is not specified in the TM1 Cfg then the default value would be 100 MB.

AuditLogMaxQueryMemory=200 MB


AuditLogUpdateInterval:

The config parameter can be used to control the amount of time the TM1 server needs to wait before moving the contents from temporary files to a final audit log file. The value is taken in minutes; that is, say 100 is entered, then it is taken has 100 minutes.

AuditLogUpdateInterval=100

 

That's it folks, hope you had learnt something new from this blog.

IBM Planning Analytics Secure Gateway Client: Steps to Set-Up

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6 min

This blog broaches all steps on how to install IBM Secure Gateway Client.

IBM Secure Gateway Client installation is one of the crucial steps towards setting up secure gateway connection between Planning Analytics Workspace (On-Cloud) and RDBMS (relational database) on-premise or on-cloud.

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What is IBM Secure Gateway :

IBM Secure Gateway for IBM Cloud service provides a quick, easy, and secure solution establishing a link between Planning Analytics on cloud and a data source. Data source can reside on an “on-premise” network or on “cloud”. Data sources like RDBMS, for example IBM DB2, Oracle database, SQL server, Teradata etc.

Secure and Persistent Connection :

A Secure Gateway, useful in importing data into TM1 and drill through capability, must be created using TurboIntegrator to access RDBMS data sources on-premise.

By deploying the light-weight and natively installed Secure Gateway Client, a secure, persistent and seamless connection can be established between your on-premises data environment and cloud.

The Process:

This is two-step process,

  1. Create Data source connection in Planning Analytics Workspace.
  2. Download and Install IBM Secure Gateway

To download IBM Secure Gateway Client.

  1. Login to Workspace ( On-Cloud)
  2. Navigate to Administrator -> Secure Gate

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Click on icon as shown below, this will prompt a pop up. One needs to select operating system and follow steps to install the client.
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Once you click, a new pop-up with come up where you are required to select the operating system where you want to install this client.

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Choose the appropriate option and click download.

If the download is defaulted to download folders you will find the software in Download folder like below.

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Installation IBM Secure Gateway Client:

To Install this tool, right click and run as administrator.

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Keep the default settings for Destination folder and Language, unless you need to modify.

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Check box below if you want this as Window Service.

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Now this is an important step, we are required to enter Gateway ids and security tokens to establish a secured connection. These needs to be copied over from Secure connection created earlier in Planning Analytics Workspace ( refer 1. Create Data source connection in workspace).

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Figure below illustrates Workspace, shared details on Gateway ID and Security Token, these needs to be copied and pasted in Secure Gateway Client (refer above illustration).

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If user chooses to launch the client with connection to multiple gateways, one needs to take care while providing the configuration values.

  1. The gateway ids need to be separated by spaces.
  2. The security tokens, acl files and log levels should to be delimited by --.
  3. If you don't want to provide any of these three values for a particular gateway, please use 'none'.
  4. If you want Client UI you may choose else select No.

Note: Please ensure that there are no residual white spaces.

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Now click Install, once this installation completes successfully, the IBM Secure Gateway Client is ready for use.

This Connection is now ready, Planning Analytics can now connect to data source residing on-premise or any other cloud infrastructure where IBM Secure Gateway client is installed.

 

You may also like reading “ Predictive & Prescriptive-Analytics ” , “ Business-intelligence vs Business-Analytics ” ,“ What is IBM Planning Analytics Local ” , “IBM TM1 10.2 vs IBM Planning Analytics”, “Little known TM1 Feature - Ad hoc Consolidations”, “IBM PA Workspace Installation & Benefits for Windows 2016”.

What is IBM Watson™ Studio?

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1 min

IBM Watson™ Studio is a platform for businesses to prepare and analyse data as well as build and train AI and machine learning models in a flexible hybrid cloud environment.

IBM Watson™ Studio enables your data scientists, application developers and subject matter experts work together easier and collaborate with the wider business, to deliver faster insights in a governed way.

Watch the below for another brief intro



Available in on the desktop which contains the most popular portions of Watson Studio Cloud to your Microsoft Windows or Apple Mac PC with IBM SPSS® Modeler, notebooks and IBM Data Refinery all within a single instal to bring you comprehensive and scalable data analysis and modelling abilities.

However, for the enterprise, there are also the versions of Watson Studio Local, which is a version of the software to be deployed on-premises inside the firewall, as well as Watson Studio Cloud is part of the IBM Cloud™, a public cloud platform. No matter which version your business may use you can start using Watson Studio Cloud and download a trial of the desktop version today!

Over the next 5 days, we'll ensure to send you use-cases and materials of worth for you to review at your earliest convenience. Be sure to check our social media pages for these.

IBM Planning Analytics (TM1) Vs Anaplan

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4 min

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IBM Planning Analytics (TM1) vs Anaplan

There has been a lot of chatter lately around IBM Planning Analytics (powered by TM1) vs Anaplan. Anaplan is a relatively new player in the market and has recently listed on NYSE. Reported Revenue in 2019 of USD 240.6M (interestingly also reported an operating loss of USD 128.3M). Compared to IBM which has a 2018 revenue of USD 79.5 Billion (there is no clear information on how much of this was from the Analytics area) with a net profit of 8.7 b). The size of global Enterprise Performance Management (EPM) is around 3.9 Billion and expected to grow to 6.0Billion by 2022. The size of spreadsheet based processes is a whopping 60 Billion (Source: IDC)

Anaplan has been borne out of the old Adaytum Planning application that was acquired by Cognos and Cognos was acquired by IBM in 2007. Anaplan also spent 176M on Sales and Marketing so most people in the industry would have heard of it or come across some form of its marketing. (Source: Anaplan.com)

I’ve decided to have a closer look at some of the crucial features and functionalities and assess how it really stacks up.

Scalability 

There are some issues around scaling up the Anaplan cubes where large datasets are under consideration (8 billion cell limit? While this sounds big, most of our clients reach this scale fairly quickly with medium complexity). With IBM Planning Analytics (TM1) there is no need to break up a cube into smaller cubes to meet data limits. Also, there is no demand to combine dimensions to a single dimension. Cubes are generally developed with business requirements in mind and not system limitations. Thereby offering superior degrees of freedom to business analyst.

For example, if enterprise wide reporting was the requirement, then the cubes may be need to be broken via a logical dimension like region of divisions. This in turn would make consolidated reporting laborious, making data slicing and dicing difficult, almost impossible.

 

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Excel Interface & Integration

Love it or hate it – Excel is the tool of choice for most analyst and finance professionals. I reckon it is unwise to offer a BI tool in today’s world without a proper excel integration.  I find Planning Analytics (TM1) users love the ability to use excel interface to slice and dice, drill up and down hierarchies and drill to data source. The ability to create interactive excel reports with ability to have cell by cell control of data and formatting is a sure-shot deal clincher.

On the other hand, on exploration realized Anaplan offers very limited Excel support.

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 Analysis & Reporting

In today’s world users have come to expect drag and drop analysis. Ability to drill down, build and analyze alternate view of the hierarchy etc “real-time”. However, if each of this query requires data to be moved around cubes and/or requires building separate cubes then it’s counterproductive. This would also increase the maintenance and data storage overheads. You also lose sight of single source of truth as your start developing multiple cubes with same data just stored in different form. This is the case with Anaplan due to the software’s intrinsic limitations.

Anaplan also requires users to invest on separate reporting layer as it lacks native reporting, dashboards and data visualizations.

This in turn results in,

  1. Increase Cost
  2. Increase Risk
  3. Increase Complexity
  4. Limited planning due to data limitations

IBM Planning Analytics, on the contrary offers out of the box ability to view & analyze all your product attributes and the ability to slice and dice via any of the attributes. 

It also comes with a rich reporting, dashboard and data visualization layer called Workspace. Planning Analytics Workspace delivers a self-service web authoring to all users. Through the Planning Analytics Workspace interface, authors have access to many visual options designed to help improve financial input templates and reports. Planning Analytics Workspace benefits include:

  1. Free-form canvas dashboard design
  2. Data entry and analysis efficiency and convenience features
  3. Capability to combine cube views, web sheets, text, images, videos, and charts
  4. Synchronised navigation for guiding consumers through an analytical story
  5. Browser and mobile operation
  6. Capability to export to PowerPoint or PDF

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Source : Planning Analytics (TM1) cube

Planning Analytics - Cloud Or On-Premise

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4 min

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This Blog details IBM Planning Analytics On-Cloud and On-Premise deployment options. It focusses & highlights key points which should help you make the decision; “whether to adopt Cloud Or stay on Premise”

 

IBM Planning Analytics:

As part of their continuous endeavour to improve application interface and better customer experience, IBM rebranded TM1 to Planning Analytics couple of years back which came with many new features and a completely new interface. With this release (PA 2.x version as it has been called), IBM is letting clients choose Planning Analytics as Local SW or as Software as a Service (SaaS) deployed on IBM Softlayer Cloud.

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Planning Analytics on Cloud:

Under this offering, Planning Analytics system operates in a remote hosted environment. Clients who choose Planning Analytics deployed “on-cloud” can reap many benefits aligned to any typical SaaS.

With this subscription, Clients’ need not worry about software Installation, versions, patches, upgrades, fixes, disaster recovery, hardware etc.

They can focus on building business models and enriching data from different source systems and give meaning to the data they have. This by converting data into business critical, meaningful, actionable insights.

Benefits:

While not a laundry list, covers significant benefits.

  • Automatic software updates and management.
  • CAPEX Free; incorporates benefits of leasing.
  • Competitiveness; long term TCO savings.
  • Costs are predictable over time.
  • Disaster recovery; with IBM’s unparalleled global datacentre reach.
  • Does not involve additional hardware costs.
  • Environment friendly; credits towards being carbon neutral.
  • Flexibility; capacity to scale up and down.
  • Increased collaboration.
  • Security; with options of premium server instances.
  • Work from anywhere; there by driving up productivity & efficiencies.

Client must have Internet connection to use SaaS and of course, Internet speed plays major role. In present world Internet connection has become a basic necessity for all organizations.

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Planning Analytics Local (On-Premise):

Planning Analytics local essentially is the traditional way of getting software installed on company’s in-house server and computing infrastructure installed either in their Data Centre or Hosted elsewhere.

In an on-premise environment - Installation, upgrade, and configuration of IBM® Planning Analytics Local software components are on the Organization.

Benefits of On-Premise:

  • Full control.
  • Higher security.
  • Confidential business information remains with in Organization network.
  • Lesser vendor dependency. 
  • Easier customization.
  • Tailored to business needs.
  • Does not require Internet connectivity, unless “anywhere” access is enabled.
  • Organization has more control over implementation process.

As evident on-premise option comes with some cons as well, few are listed below.

  • Higher upfront cost
  • Long implementation period.
  • Hardware maintenance and IT cost.
  • In-house Skills management.
  • Longer application dev cycles.
  • Robust but inflexible.

On-premise software demands constant maintenance and ongoing servicing from the company’s IT department.

Organization on on-premise have full control on the software and on its related infrastructure and can perform internal and external audits as and when needed or recommended by governing/regulatory bodies.

Before making the decision, it is also important to consider many other influencing factors; from necessary security level to the potential for customization, number of Users, modelers, administrators, size of the organization, available budget, long term benefits to the Organization.

While you ponder on this, there are many clients who have adopted a “mid-way” of hybrid environment. Under which basis factors like workload economics, application evaluation & assessment, security and risk profiles, applications are being gradually moved from on-premise to cloud in a phased manned.

 

You may also like reading “ What is IBM Planning Analytics Local ” , “IBM TM1 10.2 vs IBM Planning Analytics”, “Little known TM1 Feature - Ad hoc Consolidations”, “IBM PA Workspace Installation & Benefits for Windows 2016”.

For more Information: To check on your existing Planning Analytics (TM1) entitlements and understand how to upgrade to Planning Analytics Workspace (PAW) reach out to us at info@octanesolutions.com.au for further assistance.

Octane Software Solutions Pty Ltd is an IBM Registered Business Partner specialising in Corporate Performance Management and Business Intelligence. We provide our clients advice on best practices and help scale up applications to optimise their return on investment. Our key services include Consulting, Delivery, Support and Training. Octane has its head office in Sydney, Australia as well as offices in Canberra, Bangalore, Gurgaon, Mumbai, and Hyderabad.

To know more about us visit, OctaneSoftwareSolutions.

Is Your Data Good Enough for Business Intelligence Decisions?

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3 min

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There’s no question that more and more enterprises are employing analytics tools to help in their strategic business intelligence decisions. But there’s a problem - not all source data is of a high quality.

Poor-quality data likely can’t be validated and labelled, and more importantly, organisations can’t derive any actionable, reliable insights from it.

So how can you be confident your source data is not only accurate, but able to inform your business intelligence decisions? It starts with high-quality software.

 

Finding the right software for business intelligence

There are numerous business intelligence services on the market, but many enterprises are finding value in IBM solutions. 

IBM’s TM1 couches the power of an enterprise database in the familiar environment of an Excel-style spreadsheet. This means adoption is quick and easy, while still offering you budgeting, forecasting and financial-planning tools with complete control.

Beyond the TM1, IBM Planning Analytics takes business intelligence to the next level. The Software-as-a-Service solution gives you the power of a self-service model, while delivering data governance and reporting you can trust. It’s a robust cloud solution that is both agile while offering foresight through predictive analytics powered by IBM’s Watson.

 

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Data is only one part of the equation

But it takes more than just the data itself to make the right decisions. The data should help you make smarter decisions faster, while your business intelligence solution should make analysing the data easier. 

So how do you ensure top-notch data? Consider these elements of quality data:

  • Completeness: Missing data values aren’t uncommon in most organisations’ systems, but you can’t have a high-quality database where the business-critical information is missing.
  • Standard format: Is there a consistent structure across the data – e.g. dates in a standard format – so the information can be shared and understood?
  • Accuracy: The data must be free of typos and decimal-point errors, be up to date, and be accurate to the expected ‘real-world’ values.
  • Timeliness: Is the data ready whenever it’s needed? Any delays can have major repercussions for decision-making.
  • Consistent: Data that’s recorded across various systems should be identical. Inconsistent datasets – for example, a customer flagged as inactive in one system but active in another – degrades the quality of information.
  • Integrity: Is all the data connected and valid? If connections are broken, for example if there’s sales data but no customer attached to it, then that raises the risk of duplicating data because related records are unable to be linked.

Are you looking to harness the power of your source data to make actionable business decisions? Contact Octane to find out how we can help you leverage your data for true business intelligence.

 

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Self Service: How Big Data Analytics is Empowering Users

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3 min

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Smart businesses are seeking out new ways to leverage the benefits of their big data analytics programs, and the self-service model is coming up trumps. By placing the onus directly on business users, enterprises are empowering customers with insights-driven dashboards, reports, and more. But it’s not the only bonus. 

Arguably an even greater upside for organisations is that it alleviates the talent shortage that often comes with big data. With most companies only employing a handful of data experts who can deliver analytics insights to customers, the self-service model means they are freed up to concentrate on more important tasks, while allowing the masses to derive their own insights on their own terms. 

 

What are the real benefits of self service?

If nothing else, a self-service model creates a ‘democratisation’ of big data, giving users the freedom to access the data they need when they need it most: during the decision-making process.

Moreover, there’s a low cost to entry – coupled with reduced expenses thanks to freeing up data science and IT resources – and faster time to insight. When users know what they need and can change their research strategies according to new and changing demands, they become more empowered.

But it’s not all smooth sailing – giving customers the tools they need for self service is only one part of the equation. They must also be educated on the potential pitfalls.

 

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Avoid the common hurdles

When several users have access to specific data, there’s a risk of multiple copies being made over time, thus compromising the ‘one version of truth’ and possibly damaging any insights that could be derived.

Business users unfamiliar with big data analytics are also prone to mistakes, as they may be unaware of data-preparation complexities – not to mention their own behavioural biases. 

For all these issues, however, education is the solution, which is what Ancestry.com focused on when it began encouraging self-service analytics through its new data-visualisation platform. And with 51 quintillion cells of data you can see why.

 

There’s no harm in starting small with big data analytics

Ancestry.com has over 10 billion historical records and about 10 million registered DNA participants, according to Jose Balitactac who is the FP&A Application Manager.

The old application they were using was taking hours to do the calculations.  They looked at seven different applications before deciding on IBM Planning Analytics.  

The reason they chose IBM Planning Analytics was to accommodate the company’s super-cube of data, other solutions would have required them to “break it into smaller cubes, or reduce the number of dimensions, or join members, such as business units and cost centers.” They didn’t want to do that because their processes worked.

They set up a test with IBM to time how long it took for the model to calculate and it took less than 10-20 seconds which is what they wanted. You can read more about the Ancestry.com case study here.

If you’re keen to empower your business users through a self-service model, contact Octane today to learn how we can help you harness big data analytics.

 

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