What is the Modern Data Ecosystem?

Today’s business environment is awash with data. From product development intellectual property (IP) to customer personally identifiable information (PII) to logistics and supply chain information, data is coming at us from all directions. And that data is making its way throughout the business in ways that it never did before.

In the past, your customer and prospect data may have stayed securely behind a firewall in a customer database in a company-owned datacenter. But from the moment Salesforce launched its pioneering Software-as-a-Service CRM, that data has been moving into the cloud. And the volume has only increased. Now, cloud data platforms like Snowflake and Amazon Redshift offer anyone the ability to host and analyze data with just a credit card and a spreadsheet. This has opened a pandora’s box of data analysis possibilities that comes with attendant challenges and risks.

By now most companies understand the significant opportunities presented by living in the “Age of Data.” Recently, a data ecosystem of technologies has developed to help organizations take advantage of these new opportunities. In fact, so many new tools, solutions and technologies have appeared that choosing solutions for a modern data ecosystem can be almost as difficult as dealing with data itself.

We put together this guide to help clear the clutter and explain who does what in the modern data ecosystem and how it can help your organization become more data-driven more quickly.

Your Data Ecosystem Guide

Data Discovery, Classification, and Catalogs

The rapid growth of data collection, security threats, and regulatory requirements has transformed what was previously an esoteric process conversation into a mainstream business challenge. It’s now a strategic priority for any organization to apply and enforce data governance standards, not just the traditional regulated industries like finance and healthcare. However, data owners must tread carefully to avoid running up against privacy laws like GDPR and CCPA: Gartner believes that modern privacy regulations will cover 75% of the world in a couple of years.

Many vendors focus on “knowing” your data—where it is (discovery), what is it (classification), where it came from (data lineage). Industry analysts call this “metadata management,” or getting a handle on the data itself. Data discovery, classification and cataloging are the critical first steps of a big data ecosystem.

Alation

Alation is credited with creating the data catalog product category – an early building block of the modern data ecosystem. Its signature software, the Alation Data Catalog, serves enterprises in organizing and consolidating their data. Alation’s enterprise data catalog dramatically improves the productivity of analysts, increases the accuracy of analytics, and drives confident data-driven decision making while empowering everyone in your organization to find, understand, and govern data.

BigID

BigID offers software for managing sensitive and private data, completely rethinking data discovery and intelligence for the privacy era. BigID was the first company to deliver enterprises the technology to know their data to the level of detail, context and coverage they would need to meet core data privacy protection requirements. BigID’s data intelligence platform enables organizations to take action for privacy, protection, and perspective. Organizations can deploy BigID to proactively discover, manage, protect, and get more value from their regulated, sensitive, and personal data across their data landscape.

Collibra

Collibra calls itself “The Data Intelligence Company.” They aim to remove the complexity of data management to give you the perfect balance between powerful analytics and ease of use. The company’s premier offering is its data catalog – a single solution for teams to easily discover and access reliable data. It allows companies to provide users access to trusted data across all your data sources. Delivering this end-to-end visibility starts with your data catalog, and Collibra gets you up and running in days. With Collibra’s scalable platform, you can future-proof your investment, no matter where business takes you next.

Cloud Data Warehouses

While the cloud migration started with specific workloads moving to SaaS services (think Salesforce or Office 365), today the data ecosystem is focused on, well, data. The same advantages of SaaS – low up-front costs, no hardware to maintain, no datacenter to staff and service, no upgrades to track – all apply to the modern cloud data warehouse. In addition, data storage combined with compute enables companies to consolidate data from across the company and make it easily available for analysis and insight. Data-driven companies find this service invaluable.

Snowflake Data Cloud

Snowflake offers a cloud-based data storage and analytics service that allows users to store and analyze data using cloud-based hardware and software. Snowflake’s founders engineered Snowflake to power the Data Cloud, where thousands of organizations have smooth access to explore, share, and unlock the full value of their data. Today, 1300 Snowflake customers have more than 250PB of data managed by the Data Cloud, with more than 515 million data workloads that run each day.

Amazon Redshift

According to the company, tens of thousands of companies rely on Amazon Redshift to analyze exabytes of data with complex analytical queries, making it the most widely used cloud data warehouse. Users can run and scale analytics in seconds on all their data without having to manage a data warehouse infrastructure. Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes. With AWS-designed hardware and machine learning, the service can deliver the best price performance at any scale. The company also offers a Free Tier.  

Databricks

The Databricks Lakehouse Platform combines the best elements of data lakes and data warehouses to deliver the reliability, strong governance and performance of data warehouses with the openness, flexibility and machine learning support of data lakes.

This unified approach simplifies your modern data stack by eliminating the data silos that traditionally separate and complicate data engineering, analytics, BI, data science and machine learning. It’s built on open source and open standards to maximize flexibility. And, its common approach to data management, security and governance helps you operate more efficiently and innovate faster.

ETL and ELT Providers

Another significant piece of the data ecosystem puzzle are ETL and ELT providers. Consolidating business data in cloud data warehouses like Snowflake is a smart move that can open up new doors of innovation and value. All your data in one place makes it easier to connect the dots in ways that were impossible or unimaginable before. For instance, a retail chain can optimize sales projections by analyzing weather patterns, or a logistics company can more accurately predict costs by accounting for the salaries of all the people involved in a shipment.

Getting to those insights is a process that starts with moving the data. An extract, transform, and load (ETL) migration technology partner simplifies moving or loading the data from each of your company’s locations into a cloud data warehouse to make it analytics-ready in no time. Moving data is what these companies do best.

Matillion

Matillion’s complete data integration and transformation solution is purpose-built for the cloud and cloud data warehouses. The company’s flagship tool, Matillion ETL, is specifically for cloud database platforms including Amazon Redshift, Google BigQuery, Snowflake and Azure Synapse. It is a modern, browser-based UI, with powerful, push-down ETL/ELT functionality. Matillion ETL pushes down data transformations to your data warehouse and process millions of rows in seconds, with real-time feedback. The browser-based environment includes collaboration, version control, full-featured graphical job development, and more than 20 data read, write, join, and transform components. Users can launch and be developing ETL jobs within minutes. Matillion offers a free trial.  

Fivetran

Focused on automated data integration, Fivetran delivers ready-to-use connectors that automatically adapt as schemas and APIs change, ensuring consistent, reliable access to data. In fact, the company says it offers the industry’s best selection of fully managed connectors. Their pipelines automatically and continuously update, freeing users up to focus on game-changing insights instead of ETL. They improve the accuracy of data-driven decisions by continuously synchronizing data from source applications to any destination, allowing analysts to work with the freshest possible data. To accelerate analytics, Fivetran automates in-warehouse transformations and programmatically manages ready-to-query schemas. Fivetran offers a free trial.  

Talend

According to Talend integrating your data doesn't have to be complicated or expensive. Talend Cloud Integration Platform simplifies your ETL or ELT process, so your team can focus on other priorities. With over 900 components, you can move data from virtually any source to your data warehouse more quickly and efficiently than by hand-coding alone. Talent helps reduce spend, accelerate time to value, and deliver data you can trust.

You can download a free trial of Talend Cloud Integration.

Business Intelligence (BI) and Analytics Tools

Most business data users aren’t running database queries but accessing data and gaining insights via business intelligence tools (BI) that provide services including reporting, online analytical processing, analytics, dashboard , data mining,  complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics. As the front door to data for technical and line-of-business users throughout the company, finding a friendly, flexible, accessible BI solution is key.

Tableau

Tableau is an interactive data visualization software company focused on business intelligence. Tableau products query relational databases, online analytical processing cubes, cloud databases, and spreadsheets to generate graph-type data visualizations. The software can also extract, store, and retrieve data from an in-memory data engine. Tableau allows organizations to ensure the responsible use of data and drive better business outcomes with fully-integrated data management and governance, visual analytics and data storytelling, and collaboration—all with Salesforce’s industry-leading Einstein built right in. Companies can lower the barrier to entry for users to engage and interact by building visualizations with drag and drop, employing AI-driven statistical modeling with a few clicks, and asking questions using natural language. Tableau provides efficiencies of scale to streamline governance, security, compliance, maintenance, and support with solutions for the entire lifecycle as the trusted environment for your data and analytics—from connection, preparation, and exploration to insights, decision-making, and action.  

ThoughtSpot

ThoughtSpot believes the world would be a better place if everyone had quicker, easier access to facts. Their search and AI-driven analytics platform makes it simple for anyone across the organization to ask and answer questions with data. It empowers colleagues, partners, and customers to turn data into actionable insights via the ThoughtSpot application, embedding insights into apps like Salesforce and Slack, or building entirely new data products. The consumer-grade search and AI technology delivers true self-service analytics that anyone can use, while the developer-friendly platform ThoughtSpot Everywhere makes it easy to build interactive data apps that integrate with users’ existing cloud ecosystem.

Looker

Looker Data & Analytics is business intelligence software and big data analytics platform that helps users explore, analyze and share real-time business analytics easily. Now part of Google Cloud, it offers a wide variety of tools for relational database work, business intelligence, and other related services. Looker utilizes a simple modeling language called LookML that lets data teams define the relationships in their database so business users can explore, save, and download data with only a basic understanding of SQL.^[2] The product was the first commercially available business intelligence platform built for and aimed at scalable or massively parallel relational database management systems like Amazon Redshift, Google BigQuery and more.

Data Access Control and Data Security

ALTR is the only automated data access control and security solution that allows organizations to easily govern and protect sensitive data – enabling users to distribute more data to more end users more securely, more quickly. Hundreds of companies and thousands of users leverage ALTR’s platform to gain unparalleled visibility into data usage, automate data access controls and policy enforcement, and secure data with patented rate-limiting and tokenization-as-a-service. ALTR’s partner data ecosystem integrations with data catalogs, ETL, cloud data warehouses and BI services enable scalable on-premises-to-cloud protection. Our free integration with Snowflake allows admins to get started in minutes instead of months and scale up as you expand your data use, user base and databases.

The Evolving Data Ecosystem

ALTR continues to develop relationships with cloud data leaders across the industry. Our goal is to help our customers to get the most from their data by enabling a secure cloud data ecosystem that allows users to safely share and analyze sensitive data. Our scalable cloud platform acts as the foundation by enabling seamless integration with a wide variety of enterprise tools used to ingest, transform, store, govern, secure, and analyze data. ALTR has expanded how we interact with data ecosystem leaders via open-source integrations that allow users to freely and easily extend ALTR's data control and security to data catalogs like Alation and ETL tools like Matillion. Building a modern data ecosystem stack will set you firmly on the path to secure data-driven leadership.