Posts

Looking back now that we’ve reached the one year anniversary of the Take30, we appreciated the opportunity to share our perspective on a range of Business Intelligence (BI) topics with a wide and diverse audience.  

The topics we covered ranged from the strategic and thought provoking, to the deep technical and “how-to” with a consistent focus on how to improve the analytics experience for you and your user community.

Over the course of the year we hosted 28 sessions focused on BI, most were either focused on a specific technology (Amazon QuickSight, IBM Cognos, Microsoft Power BI or Tableau) or a comparison on how these technologies addressed a capability such as Natural Language Query (NLQ), Embedded Analytics or Cloud BI.

Many of our sessions focused on our heritage as the go-to Cognos experts including deep dives into the modern BI features in Cognos Analytics including Data Modules, Data Sets and Explorations.  In one of our most highly anticipated (and highly attended) sessions, Rachel Su from IBM Offering Management joined Ironside to lead an overview of Cognos Analytics 11.1.7 – a role she reprised last month for Cognos Analytics 11.2).

In a number of other sessions, we explored Tableau new features, touched on many of the enterprise capabilities of Power BI and introduced Amazon QuickSight to our audience. 

Creating a Centralized Metadata Model in Power BI (4/16/20)

In our first session of the Take30 series, we explored the concept of shared datasets in Power BI and offered our point of view that, for many organizations who are maturing their Power BI capabilities, shared datasets mapped well to the “traditional” approaches of centralized (and governed) metadata, yet offered a degree of flexibility for decentralized teams to move at their own pace.  (Checkout this Playlist for Power BI)

Cloud BI: A Comparison of Leading Technologies (6/25/20)

As a majority of organizations see Cloud-based analytics as critical to their current and future analytics strategies, we thought it an opportune moment to take our audience through a review of the leading BI tools we work with on a daily basis.  

We reviewed the benefits of Cloud BI, including serverless and subscription-based licensing, then provided a comparison of vendors including Microsoft Power BI, Tableau, IBM Cognos and Amazon QuickSight.  

Amazon QuickSight – New Features (10/1/20)

While relatively new to the BI marketplace, we were excited to continue our focus on Amazon QuickSight and the significant progress the AWS team is making toward a solid enterprise featureset.  

Since that time, the roadmap and feature releases have become even more aligned to the enterprise reporting use case, especially in consideration of the compelling licensing story and scalable serverless architecture on which it is based.  (you may also want to check out this intro to QuickSight session  Introduction to Amazon QuickSight (5/7/20))

Enterprise Reporting: Assessment, Simplification and Migration (2/18/21)

Lastly, we wanted to address a topic that is of increasing prominence in our day to day conversations with clients – that of enterprise reporting migrations.  

In this session, we provided our point of view on the reasons why organizations migrate from their legacy tools, offered perspectives on approaches to migrations and the important pitfalls and lessons learned when considering such an initiative. 

We touched on tooling and accelerators we’ve developed to help those who have embarked on this journey reach their destination more quickly.

____

Throughout 2020, the Take30 webinar series gave our BI Experts a new way to connect with our clients and prospects in what was otherwise a challenging year. We confirmed that our participants are not only interested in diving deep into tool functionality, they are looking for guidance in managing multiple BI tools at enterprise scale, and understanding how cloud BI can enhance their analytics capabilities without breaking enterprise reports and functionality which are critical to their business operation.

Looking forward, we are going to explore those and other questions with you as we continue to share our knowledge and provide a mix of content; from the tactical to the strategic, across all the tools we help our clients with on a daily basis.

The Ironside Take30 webinar series premiered on April 16th, 2020, with the goal to share expert dialog across a variety of data and analytics related topics to a wide range of audiences. The series has three primary dialog categories, each hosted by a BI Expert, Data Scientist or Data Advisor. In the past year, we’ve shared best practices with over 200 companies ranging from Fortune 50 to small businesses. Our success has been measured by participants returning and telling a colleague; on average, each unique company attended over six Take30 sessions. 

While some Data Advisor sessions are more technical, the focus is on describing concepts and tools at a less detailed level. We want to give people a sense of how rapidly the data and analytics environment is changing. To that end, the Data Advisor series worked with our partners, including IBM, AWS, Snowflake, Matillion, Precisely and Trifacta, to bring demonstrations of their tools and discuss the impact of their capabilities. We talked about the rapid expansion both of data and of the solution space to move, structure, and analyze that data. 

Most importantly, we had a special series on the Modern Analytics Framework, Ironside’s vision for and approach to a unified approach to insight generation that puts the right data in the hands of the right people. Regardless of your industry, your tools, or your use cases, you need a way to keep your data, users, and processes organized.

“What do you need in your data warehouse?” used to be the chief question asked when thinking about data for analytics. That time is past. Now, a data warehouse is just one possible source of analytics. Most organizations have so much data that building a warehouse to contain all of it would be impossible. At the same time, data lakes have emerged as a popular option. They can easily hold vast amounts of data regardless of structure or source. But that doesn’t mean the data is easy to analyze. 

And just as there’s no longer a single question to ask about structuring data, there’s no longer just one voice asking the question. Data scientists and data engineers are among the many personas that have emerged as consumers of data. Each has their own toolset(s) and preferences for how data should look for their purposes. 

All of this diversity demands a more distributed approach to ingesting, transforming and storing data – as well as robust and flexible governance to manage it. All of the topics covered in the past year of Take30 with a Data Advisor touch on these points, and on Ironside’s goal to help you make better decisions using your data.  Here are five of the 27 Data Advisor sessions we hosted this year: 

  • Modern Analytics Framework: Series Summary  (7/30/20-9/1/21) – This 6-part series covers all aspects of Ironside’s Modern Analytics Framework: overall concepts, assessment and design, governance, identification of user personas, implementation, and usage. If you are looking to upgrade your existing analytics environment, or creating one for the first time, this is an essential series, and one that Ironside will be expanding on in 2021.

  • Snowflake as a Data Wrangling Sandbox (6/3/20) – Snowflake is a tremendous cloud database platform for data storage and transformation. Its complete separation of compute and storage allows for many usage scenarios, and most importantly for easily scalability based on volume of data and consumption. Nirav Valia (from Ironside’s Information Management practice) presents on one common Snowflake use case: using Snowflake as a data wrangling sandbox. Data wrangling typically involves unpredictable consumption patterns and creation of new data sets, as an analyst seeks to discover new insights or answer new questions by manipulating data sets. Snowflake’s power and flexibility easily handles these types of activities without requiring up-front investment or significant recurring costs. It’s easy to create transformations, let them run, then let the data sit until it is needed again. (If you are interested in Snowflake, also consider our later Take30 Snowflake: Best Practices (9/24/20), including commentary from a Snowflake engineer.) 

  • What is Analytics Modernization? How can Data Prep Accelerate It? (with Trifacta) (2/4/21) – Toward the end of our first year of Take 30s, we held a panel, hosted by Monte Montemayor of Trifacta, around data prep and accelerating analytics modernization. As I mentioned earlier, there is a tremendous amount of data available today – but getting it analytics-ready is a huge challenge. Tools like Trifacta (known as Advanced Data Prep, or ADP, in the IBM world) are extremely useful for giving analysts and business users the ability to visualize and address data quality issues in an automated fashion. This is useful for data science, dashboarding, data warehouses – any place where data is consumed. (If you are interested in Data Prep, check out IBM Advanced Data Prep in Action (7/8/20) and Data Wrangling made Simple and Flexible with Trifacta (5/6/20))

  • A Data Warehousing Perspective: What is IBM Cloud Pak™ for Data? (5/27/20) – IBM has created a single platform for data and analytics that works across cloud vendors and on-premise. If you want to be able to shift workload between local nodes and the cloud easily, this is the solution for you. In this Take30, we provide an overview of the technologies that make Cloud Pak for Data possible, and how you can take advantage of them. (We also have a session Netezza is back, and in the cloud (7/23/20) discussing Netezza, one of the many technologies available on the Cloud Pak platform)

  • A Data Strategy to Empower Analytics in Higher Ed (7/1/20) – Occasionally, we have the opportunity to host an industry-specific Take30, and where possible, we have clients join us. Northeastern University joins this Higher Ed focused Take30 to discuss their approach taken with Ironside in developing a multi-year roadmap. This was geared towards increasing the “democratization of data and analytics” by establishing the organizational foundation, technology stack and governance plan necessary to grow self service throughout the institution. Our discussion highlights the particular challenges of a decentralized, highly autonomous structure, and shared the value of a data science pilot in the admissions area executed during the strategy engagement to generate tangible results.

2020 was a unique year. At Ironside, it gave us the opportunity to reach out to customers in a new way – one that we are continuing into 2021. We look forward to more detailed sessions on the Modern Analytics Framework, and on trends and tools that we see gaining prominence. 

After a year of delivering these sessions, we’ve realized that customers are not only looking for specific solutions, but for a sense of where the analytics world is going. Which cloud platforms make the most sense? What transformation and data wrangling tools are the most useful? Should I redesign my warehouse or just add a data lake? We look forward to exploring those and other questions with you.