In our blog post Choosing the Right Database for Your Data Strategy, we provided a strategy in how to choose an operational database that will suit your company’s long-term needs. As an operational database is crucial for processing and storing transactional data, like product usage or contact information, data warehouses play an integral role in turning static data into insights.
Data plays a critical role in running a business. As a data analyst, you understand the importance of data. But sometimes, it can be difficult to turn your technical aptitude into business insights.
As data analysts evaluate user behavior through analytics tools, business users are interested in understanding the performance of their efforts—whether it’s Sales, Marketing or Customer Success.
Much like your company’s data, a data analyst cannot be siloed into his or her own world, running analyses separate from business conversations.
Data is your company’s most valuable asset. In using data, Executives are able to accurately forecast revenue and marketers are able to run efficient campaigns. Without data, we’d all be going at it blind.
To unlock the full reach of your data, you need to make sure it’s extracted, processed, consolidated and transformed into insights. The key here is consolidating data from various sources. So, instead of drudging through different data sources and working in a vacuum, it’s time to bring data together.
Databases are more than columns and rows. Whether you’re a scaling SaaS business or a Fortune 500 company, you’ll need a way to store all your data from email marketing lists to user IDs. Choosing the right database is a long term decision that will impact your business. You don’t want to start out on the path of implementing a database that your business will outgrow in a few months. And, rethinking your entire database strategy down the road isn’t ideal.
I closed-out my first year after receiving my Bachelors Degree, in command of a 3-person team, tasked to regularly go forward of most infantry assets in providing forward reconnaissance, all while carrying well over a couple million dollars-worth of “sensitive” communications gear. I was just a young kid thrust into an extraordinary situation based on the needs of his chain of command.
The business world of today is a far cry from the stresses of the modern battlefield. It’s considerably more beneficial to a person’s health and well-being than a tour in a combat zone, but there is one aspect that is constant in both environments: Decision-Paralysis – over-analyzing a situation to the point that a decision is never taken.
I recently spoke at the community meetup for the MADlib Apache incubator project, an open source library for scalable in-database analytics.
If you've never heard of MADlib and you use PostgreSQL, Greenplum or HAWQ (also an Apache incubator project) then you should definitely check it out. It's a database extension that allows you to perform advanced statistical and machine learning computations within your database where your data resides...
Do you find it hard to concentrate in a disorganized environment? According to Cole Nussbaumer Knaflic of the recently published book Storytelling with data: a data visualization guide for business professionals, 75% of people have a hard time focusing in a cluttered environment and that number increases to 87% when it comes to visualizing data.
What does this mean? A messy dashboard with many colors and charts can seriously affect how your audience interprets the message you are trying to convey.
Check out our post to learn the top 5 tips to decluttering and grabbing your audience's attention.
We’re excited to interview William Chen, Data Scientist at Quora. William also contributes heavily to Quora’s community by writing extensively about Data Science, Statistics, Data Analysis, Machine Learning, and Probability.
If you’re whirling around in the 1.0 world, you might be a fan of measuring dials (dials per hour reps are doing). It's a useful metric when you’re training new reps and one that measures activity. But once a rep ramps up their pipelines, are you still using dials as a way to track results? What about number of appointments? Is the appointment metric important to you? Does that really give you the data you need to more accurately forecast opportunities?
Now that we have covered best practices for creating a framework for your dashboard, this last post will cover how to make your dashboard a beautiful visualization.
Now that we have established the purpose of the dashboard, start thinking about how the dashboard’s layout will best serve the audience and provide value. This is the first step toward thinking about how the dashboard looks and how it will function.
Your business intelligence dashboard is the portal to your most important business metrics and insights. It can be the daily gateway into your team's activities, the scoreboard for your organizational goals, or a way for your company’s stakeholders to find new insights.
Chris Winslett, product manager at Compose, joined Chartio's AJ Welch for a webinar on why a company with deep roots in NoSQL chose PostgreSQL for its analytics database. AJ followed up with a live demonstration of how to use MoSQL to build a Postgres database from your MongoDB data.
It’s critical to remember that data quality is a continual process that requires diligence from everyone in your organization. Use our steps to maintain data quality as a pillar of your data management system.
Hubspot does a good job of managing marketing lists. It's extraordinarily flexible in defining email lists for your promotions and nurturing campaigns. But if you want to test a list or a promotion, there's no way inside of Hubspot to select a portion of your list (say, 10%) and either send the remainder your standard email or reserve it for other promotions in the future
As you manage your data, make sure that the causes of errors are not only detected and corrected, but the process of collecting and managing the data is improved to prevent future errors and maintain a sound data system.
Chartio's customers are big users of Amazon Redshift as a data source, so we were pleased to host Tina Adams, product manager of the Redshift team at our most recent customer meetup. Tina introduced us to user-defined functions in Redshift, reviewed some of their best practices, and took questions from the audience.
To be successful at running a business you need to use data to make important decisions. You go through a continual process of collecting, updating, and creating data in order to have the insights that help you grow and succeed. The quality of the data your company uses is essential to the reliability of your business analytics and business intelligence.
Over the past five years or so, I’ve noticed the perception that relational databases are only good at descriptive statistics (count, sum, avg, etc.) on medium sized structured data sets. In other words, SQL just doesn’t work for inferential, predictive or causal analysis on larger or unstructured data sets. Although this may have been true five years ago, it’s a lot less true today.
We’re excited to announce that in our first year of participation in the annual BARC survey of BI users, Chartio was the top-ranked tool in four KPI’s and a leader 15 others in its peer group in the fourteenth annual BARC survey of BI users.