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Will real-time data processing replace batch processing?
At Confluent's user conference, Kafka co-creator Jay Kreps argued that stream processing would eventually supplant traditional methods of batch processing altogether.
Absolutely: Businesses operate in real-time and are looking to move their IT systems to real-time capabilities.
0%
Eventually: Enterprises will adopt technology slowly, so batch processing will be around for several more years.
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No way: Stream processing is a niche, and there will always be cases where batch processing is the only option.
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Data

If Your Data Isn’t Answering ‘Why,’ It Isn’t Working Hard Enough

Understanding the why behind our data at Landing has transformed our business into an organization that is able to quickly pivot and evolve.
Jul 22nd, 2022 8:15am by
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We have passed a point in this new era of data where simply having a lot of data is no longer enough. Most organizations know it’s critical to better leverage the data they’ve been collecting to make the right decisions and take action.

Dave Aaron
Dave is the head of data and analytics at Landing, a network of fully furnished apartments in more than 375 cities across the country. Prior to joining Landing, Dave spent eight years with Wayfair developing BI and analytics solutions. He resides in Boston, Massachusetts, with his wife and children.

To do this, organizations need their data strategy to be as self-service as possible so analysts can quickly provide business-critical answers to stakeholders and focus on more strategic and proactive initiatives.

At Landing, a nationwide subscription service offering furnished flexible-lease apartments, we use category-leading tools such as Stitch, Snowflake, dbt and Looker to automate, store, model, feed, explore and visualize our data.

While this data stack helps us monitor what is happening, it’s also essential for us to understand why things happen within key business metrics in order to determine the root cause and make the correct decisions about what to do next. This is why we added Sisu to our data stack — to accelerate data investigation and quickly surface the drivers of change in our business’s key metrics.

Since adding Sisu, we’ve been able to solve conversion decreases more quickly for reasons including call center staffing shortages, which enables stakeholders to develop contingency plans to avoid similar conversion declines in the future. Additionally, we leveraged the machine learning-powered insights from Sisu to spur discussion around cyclical demand and supply trends. This helped optimize our monthly acquisition spend, resulting in a 9% gain in efficiency during certain periods each month.

Bringing the Sisu Decision Intelligence Engine into our analytics workflows was a catalyst for bringing insights on key performance metrics, such as reservation volume and conversion rates, into our business meeting workflow. This collaborative process has given stakeholders the fast answers they need to act on the factors causing metric change. Not only does Sisu save our Business Intelligence (BI) team’s time, but the company as a whole has gained efficiency through the optimization and changes we’ve been able to make that stemmed from Sisu analyses.

So, how’d we do it?

Every Monday, the Landing BI team jumps into the Sisu Decision Intelligence Engine to investigate and analyze period-over-period drivers of change in our key metrics. This helps us focus and drill into the different drivers of change to pull out significant facts and determine underlying causes. Then we meet with internal stakeholders across marketing, product and sales to discuss our findings and potential impacts or shifts in strategy. Our BI team then packages the insights and recommendations, based on the data, which stakeholders use to either correct negative trends or capitalize on positive ones. Typically by this point, the team has spent less than 24 hours identifying key changes, presenting them and developing data-driven recommendations for stakeholders to use against those key metrics. By Wednesday, our executives are digesting this information and taking action on how to best course-correct or optimize the drivers of change.

Understanding the why behind our data at Landing has transformed our business into an organization that is able to quickly pivot and evolve. Gone are the weeks we’d spend slicing up data in a million ways to hypothesize why something went right or wrong. The addition of Sisu to our stack allows us to optimize our comprehensive data investments and create even more value, unlocking a new modern data stack that puts the power of data in the hands of everyone.

Whether you are an organization just beginning your data journey or are looking to get even more business value out of your data, check out our latest webinar with Sisu to learn more about how we built data into our business workflows to ensure we’re quickly surfacing why metrics change, and acting on the factors that affect our business.

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TNS owner Insight Partners is an investor in: Pragma.
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