Congratulations to each and every one of you on making it through the toughest year I could have ever imagined. This year has been filled with so much pain, disappointment and fear, but now that we are nearing the end, I cannot say anything other than congratulations and thank you for banding together in a year that completely re-engineered the way many of us think.
Personally, there’s not much else I can say for this year. Professionally, I have seen this year become the inflection point some needed to make data the beating heart of their organization. It’s undeniable that COVID-19 accelerated digital transformation exponentially, and as we see what 2021 looks like for this industry, it seems much more mature than in years past.
Last year, when I was sitting down to write this blog, the landscape for data analytics was much smaller. At the beginning of 2020, we identified a few areas to focus on in the new year. Looking at that list as an architect or engineer at InterWorks in 2020 meant a few things:
- Be forward thinking – Pay attention to streaming and event-driven architectures that offer efficiencies and scalability.
- Be at the cutting edge – As Snowflake matures into its role as the Data Cloud, new worlds have opened inside of the platform. Being ready to assist customers along any number of data journeys is our privilege and opportunity.
- Be an expert tactician – Cloud technology is now catering to organizations of all shapes and sizes. Architecture and delivery of cost-efficient, reliable systems open up a world of opportunity for our clients and our practices.
- Be nice – Every client we work with is at a different stage in their own data journey. It is our job to help them along that path and to have a good while attitude doing it.
With this vision in mind, 2020 showed us that at the core of what makes InterWorks different is our entrepreneurial, disruptive nature. In 2020, our data practice strived to separate ourselves from competitors by being “Small Giants”. As we move into 2021, we have new predictions and ideas about how organizations will continue to use and provide value using data.
In 2021, we have one goal: continue the momentum of establishing ourselves as the best data consultancy in the world. Looking at how data has changed over the years, it is undeniable that managing, presenting and monetizing data completely changes the value of a business. Additionally, this past year showed us that the modern enterprise of any size has the opportunity to do more with data than they are doing today. Looking at what’s on the horizon, we are starting the year with a few focal points:
- Educate our clients on the value available through the ever-expanding data cloud
- Guide the way organizations use data with new processing patterns
- Grow awareness on simplified machine-learning use cases that can deliver value
- Continue the trajectory we are seeing in cloud adoption
Data Cloud Expansion
“Data is the beating heart of the modern enterprise”
– Frank Slootman, CEO & President of Snowflake
Snowflake the Data Cloud is expanding. If it wasn’t made obvious by the largest software IPO in history, the company really is here to reimagine the way organizations use and derive value from their data. Workloads that have always been fundamentally possible because of Snowflake’s architecture are getting the spotlight they deserve, sharing how organizations can expand their ability to utilize data in interesting ways. Snowflake’s ability to support data engineering, data sharing, data application, data science, data lake and the data warehouse is beginning to clarify the organization’s strategic vision for how they use data. We specifically believe that data sharing is poised to revolutionize the way people consume and share data in the coming year, and we have some exciting projects in the works to bring that vision to life. As the data cloud ecosystem is expanding, InterWorks is heavily investing in enablement and infrastructure to best equip our team to be a strategic partner for organizations in any one of these areas.
Using Data in Different Ways
This year, we have seen a new line of thought emerge for how organizations work and develop solutions with data. Traditionally, data science and data engineering workloads have seemed inherently different. One camp heavily invests in the development of solutions using pure SQL, applying transformations and business logic in the universal language of data. The other opts for a more programmatic approach, transferring datasets into formats like the data frame and performing advanced analytics in a more traditional programming language like Java, Python or Scala.
For as long as I have been in this industry, the belief has been that the problem of advanced analytics was so fundamentally different that it required an entirely different set of tools from the ground up to service them. For lack of a better word, a “silo” of storage, compute and programming resources with the sole purpose of powering these workloads. The introduction of SnowPark challenges this notion, and I agree with the principle. Now more than ever, organizations are going to need a single reliable source of truth to power all of their data needs. Integrating advanced analytics as a piece of your company’s data platform will be key for long-term success, and we are equipped to advise on exactly how to do this.
Simplified Machine Learning
“The definition of genius is taking the complex and making it simple.” – Albert Einstein
Similar to the way Snowflake made data warehousing workloads accessible to organizations of all shapes and sizes, there are a number or tools tackling the same problem for machine learning and data science. For a long time, the argument for machine learning has been tone deaf. Examples of organizations like Uber and Lyft using machine learning as a competitive advantage are amazing but do not address the needs of companies that weren’t born in the cloud. Amazon SageMaker, DataRobot and others are working hard to remove the barriers to machine learning, proving that you do not need a PhD in mathematics on staff to develop solutions in this area. In 2021, I fully expect to come in contact with organizations of all shapes and sizes looking to better understand how machine learning can provide value to their business, and with an expanding ecosystem of tools to simplify this process, machine learning is poised to take the data world by storm. Machine learning is becoming simpler, and that is a good thing for everyone.
Cloud technology is not new, but COVID-19 accelerated adoption in a way we could not have fathomed at this time last year. I am constantly working with clients to design solutions that fit their needs, and up until this year, the question of “Do you have restrictions against using cloud technology?” was constantly asked in our initial conversations. In recent months, the answer to that question has been no for the most part, and now it is something that seems relevant only in certain situations. Organizations are looking to modernize the way they do business and collect and monetize data. I have long held the belief that analytics was the perfect application of cloud technology. Familiar needs like speed, scalability, efficiency and cost were all front of mind when the pandemic produced the need for solutions that would not have been possible with traditional on-prem infrastructure. As our clients looked to the cloud, we were ready to provide guidance. This push now has organizations evaluating successful deployments from COVID-19 and is raising questions about inefficiencies that might lie in their legacy tech stack. How could we be better?
At InterWorks, we have always been equipped to assist organizations in their data journey, often times using tools in the cloud. This year has produced the opportunity for us to not only design data solutions in the cloud, but also to position ourselves as the go-to partner when determining how to make cloud investments across the IT ecosystem. In the new year, cloud skills will be crucial to the portrait of an InterWorks consultant, and we are ready to assist our clients in tool selection, architecture and security as they migrate and re-platform existing workloads into AWS, Azure, GCP and Snowflake.
Tackling These Data Goals in 2021
In this new year, we are thrilled to continue studying technology we love in order to solve the data problems of the world. Let’s make this the best year yet!