How Acceldata Is Changing the Way Organizations View and Value Their Data

SAN JOSE, CA / ACCESSWIRE / August 16, 2021 / Most organizations lack the tools and expertise to capture and understand the vast volumes of data they produce every day. And even where in-house data-collection and data-processing expertise exists, senior leaders often express discomfort or bewilderment on the subject - stunting the development of the insight-driven cultures they know they need to nurture.

These are among the sobering takeaways from a recent Deloitte survey of corporate leaders. A clear majority (63%) of senior executives believe their organizations aren't sufficiently insight-driven, while two-thirds (67%) are uncomfortable accessing or using data.

Deloitte's findings suggest that it's not enough to invest in data infrastructure. According to a recent piece in the Harvard Business Review, the vast majority of large enterprises (91.9%) surveyed by NewVantage Partners accelerated investments in data infrastructure in 2020, yet fewer than 30% reported "transformational business outcomes" as a result. More troublingly, just 24% of respondents characterized their organizations as "data-driven," down sharply from nearly 38% a year earlier.

Something isn't clicking.

The Data Gap Is Getting Worse

Acceldata co-founders Rohit Choudhary, Ashwin Rajeeva, Gaurav Nagar, and Raghu Mitra Kandikonda know more about this state of affairs than just about anyone else. For years, they worked or consulted for ostensibly data-savvy companies - including tech giants like Hortonworks, InMobi, and Citrix - that struggled to collect and synthesize information.

During their careers, time and again the strategic data initiatives at their companies failed, which wasted tens or even hundreds of millions in the process. The blame always seemed to fall on outdated tools that simply weren't up to the task of corralling vast amounts of data and transforming those signals into actionable intelligence.

Amid growing data workloads and multiplying data-reliant processes, this data gap represented a worsening competitive threat for the afflicted companies. In an ever more treacherous digital threat landscape, it also presented an unacceptable risk to business continuity.

Data Observability: The Key to a Data-Driven Future

Determined to arm enterprises against this potentially existential threat, Choudhary et al set about building the planet's most comprehensive data observability platform. Launched as Acceldata in 2018, their solution takes a holistic approach to deliver end to end visibility across hybrid data pipelines. Data pipelines are like supply chains for modern, data-driven enterprises. When data pipelines break, business slows down, or even worse, grinds to a halt. Acceldata gives organizations a single view to improve reliability, accelerate scale, and reduce costs across the data compute layer, the data layer, and data pipelines.

In short order, Acceldata has become the go-to data observability solution for enterprises serious about closing the data gap. The company serves some of the biggest names in business: PhonePe (a Walmart company), Oracle, Pubmatic, General Electric, among others.

The reasons for Acceldata's early momentum are clear. As organizations are migrating to the cloud, data observability is a key ingredient to make sure that the migrations are successful and cost effective. The company is driving a transformation in how organizations can use an AI/ML based platform to predict and prevent operational issues before they impact business outcomes, detect anomalies in data at rest and in motion, and implement data governance at scale.

Those that utilize Acceldata's efforts are already realizing significant value and ROI from their data pipelines. One Acceldata client, PhonePe (a Walmart company), used its data observability solution to identify problematic infrastructure issues and seasonal and campaign based deviations, sparing the company a costly and time-consuming troubleshooting campaign. PhonePe leveraged Acceldata's capabilities to scale data infrastructure by 10 times, lending a hand to an enormous business expansion.

The headline result was impressive. PhonePe saved more than 5 million in annual software licensing costs. But Acceldata also helped PhonePe achieve a feat that can't be quantified in financial reports: It minimized the unit's daily firefighting by improving engineering productivity. By reducing expenses and bringing a previously unimaginable level of efficiency to PhonePe's Big Data infrastructure, the campaign significantly improved the unit's ROI - no small thing in a corporate culture famous for prizing the concept of "continuous improvement" above all else.

Data Observability for Every Enterprise

PhonePe is just one of dozens of companies that use Acceldata's solutions to manage and master their data, and its success is just one part of a much larger story.

The versatility of its solutions is critical to Acceldata's appeal to prospective clients and investors. Acceldata meets firms where they're at, delivering insights on data flows and events from platforms like Apache NiFi, Kafka, Spark Streaming, Kafka, Hive, Flink, and Google Dataproc. For a first mover in the data observability space, it's a surprisingly comprehensive product - an attribute that no doubt plays an outsize role in its early success.

Perhaps most importantly, Acceldata empowers its users to create sustainable data-driven infrastructures and cultures that leave them more flexible and competitive than before. By centralizing data and workload management and recommending ideal configurations for data processing, its solutions bring order and reduce data silos - paving the way for system reliability, scalable performance and optimized costs for data ops teams, data scientists, business users and executives.

Acceldata's success demonstrates that data observability is much more than a buzzword. It's essential to a data-driven future, and it's within reach for any enterprise that wants it.

CONTACT

Loretta Jones
loretta@acceldata.io

SOURCE: Acceldata



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